Parallel magnetic resonance imaging using coils with localized sensitivities.

PubMed

Goldfarb, James W; Holland, Agnes E

2004-09-01

The purpose of this study was to present clinical examples and illustrate the inefficiencies of a conventional reconstruction using a commercially available phased array coil with localized sensitivities. Five patients were imaged at 1.5 T using a cardiac-synchronized gadolinium-enhanced acquisition and a commercially available four-element phased array coil. Four unique sets of images were reconstructed from the acquired k-space data: (a) sum-of-squares image using four elements of the coil; localized sum-of-squares images from the (b) anterior coils and (c) posterior coils and a (c) local reconstruction. Images were analyzed for artifacts and usable field-of-view. Conventional image reconstruction produced images with fold-over artifacts in all cases spanning a portion of the image (mean 90 mm; range 36-126 mm). The local reconstruction removed fold-over artifacts and resulted in an effective increase in the field-of-view (mean 50%; range 20-70%). Commercially available phased array coils do not always have overlapping sensitivities. Fold-over artifacts can be removed using an alternate reconstruction method. When assessing the advantages of parallel imaging techniques, gains achieved using techniques such as SENSE and SMASH should be gauged against the acquisition time of the localized method rather than the conventional sum-of-squares method.

Experimental study on the sensitive depth of backwards detected light in turbid media.

PubMed

Zhang, Yunyao; Huang, Liqing; Zhang, Ning; Tian, Heng; Zhu, Jingping

2018-05-28

In the recent past, optical spectroscopy and imaging methods for biomedical diagnosis and target enhancing have been widely researched. The challenge to improve the performance of these methods is to know the sensitive depth of the backwards detected light well. Former research mainly employed a Monte Carlo method to run simulations to statistically describe the light sensitive depth. An experimental method for investigating the sensitive depth was developed and is presented here. An absorption plate was employed to remove all the light that may have travelled deeper than the plate, leaving only the light which cannot reach the plate. By measuring the received backwards light intensity and the depth between the probe and the plate, the light intensity distribution along the depth dimension can be achieved. The depth with the maximum light intensity was recorded as the sensitive depth. The experimental results showed that the maximum light intensity was nearly the same in a short depth range. It could be deduced that the sensitive depth was a range, rather than a single depth. This sensitive depth range as well as its central depth increased consistently with the increasing source-detection distance. Relationships between sensitive depth and optical properties were also investigated. It also showed that the reduced scattering coefficient affects the central sensitive depth and the range of the sensitive depth more than the absorption coefficient, so they cannot be simply added as reduced distinct coefficients to describe the sensitive depth. This study provides an efficient method for investigation of sensitive depth. It may facilitate the development of spectroscopy and imaging techniques for biomedical diagnosis and underwater imaging.

Highly sensitive image-derived indices of water-stressed plants using hyperspectral imaging in SWIR and histogram analysis

PubMed Central

Kim, David M.; Zhang, Hairong; Zhou, Haiying; Du, Tommy; Wu, Qian; Mockler, Todd C.; Berezin, Mikhail Y.

2015-01-01

The optical signature of leaves is an important monitoring and predictive parameter for a variety of biotic and abiotic stresses, including drought. Such signatures derived from spectroscopic measurements provide vegetation indices – a quantitative method for assessing plant health. However, the commonly used metrics suffer from low sensitivity. Relatively small changes in water content in moderately stressed plants demand high-contrast imaging to distinguish affected plants. We present a new approach in deriving sensitive indices using hyperspectral imaging in a short-wave infrared range from 800 nm to 1600 nm. Our method, based on high spectral resolution (1.56 nm) instrumentation and image processing algorithms (quantitative histogram analysis), enables us to distinguish a moderate water stress equivalent of 20% relative water content (RWC). The identified image-derived indices 15XX nm/14XX nm (i.e. 1529 nm/1416 nm) were superior to common vegetation indices, such as WBI, MSI, and NDWI, with significantly better sensitivity, enabling early diagnostics of plant health. PMID:26531782

A novel class sensitive hashing technique for large-scale content-based remote sensing image retrieval

NASA Astrophysics Data System (ADS)

Reato, Thomas; Demir, Begüm; Bruzzone, Lorenzo

2017-10-01

This paper presents a novel class sensitive hashing technique in the framework of large-scale content-based remote sensing (RS) image retrieval. The proposed technique aims at representing each image with multi-hash codes, each of which corresponds to a primitive (i.e., land cover class) present in the image. To this end, the proposed method consists of a three-steps algorithm. The first step is devoted to characterize each image by primitive class descriptors. These descriptors are obtained through a supervised approach, which initially extracts the image regions and their descriptors that are then associated with primitives present in the images. This step requires a set of annotated training regions to define primitive classes. A correspondence between the regions of an image and the primitive classes is built based on the probability of each primitive class to be present at each region. All the regions belonging to the specific primitive class with a probability higher than a given threshold are highly representative of that class. Thus, the average value of the descriptors of these regions is used to characterize that primitive. In the second step, the descriptors of primitive classes are transformed into multi-hash codes to represent each image. This is achieved by adapting the kernel-based supervised locality sensitive hashing method to multi-code hashing problems. The first two steps of the proposed technique, unlike the standard hashing methods, allow one to represent each image by a set of primitive class sensitive descriptors and their hash codes. Then, in the last step, the images in the archive that are very similar to a query image are retrieved based on a multi-hash-code-matching scheme. Experimental results obtained on an archive of aerial images confirm the effectiveness of the proposed technique in terms of retrieval accuracy when compared to the standard hashing methods.

X-ray Scatter Imaging of Hepatocellular Carcinoma in a Mouse Model Using Nanoparticle Contrast Agents

NASA Astrophysics Data System (ADS)

Rand, Danielle; Derdak, Zoltan; Carlson, Rolf; Wands, Jack R.; Rose-Petruck, Christoph

2015-10-01

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors worldwide and is almost uniformly fatal. Current methods of detection include ultrasound examination and imaging by CT scan or MRI; however, these techniques are problematic in terms of sensitivity and specificity, and the detection of early tumors (<1 cm diameter) has proven elusive. Better, more specific, and more sensitive detection methods are therefore urgently needed. Here we discuss the application of a newly developed x-ray imaging technique called Spatial Frequency Heterodyne Imaging (SFHI) for the early detection of HCC. SFHI uses x-rays scattered by an object to form an image and is more sensitive than conventional absorption-based x-radiography. We show that tissues labeled in vivo with gold nanoparticle contrast agents can be detected using SFHI. We also demonstrate that directed targeting and SFHI of HCC tumors in a mouse model is possible through the use of HCC-specific antibodies. The enhanced sensitivity of SFHI relative to currently available techniques enables the x-ray imaging of tumors that are just a few millimeters in diameter and substantially reduces the amount of nanoparticle contrast agent required for intravenous injection relative to absorption-based x-ray imaging.

Estimation of Spatiotemporal Sensitivity Using Band-limited Signals with No Additional Acquisitions for k-t Parallel Imaging.

PubMed

Takeshima, Hidenori; Saitoh, Kanako; Nitta, Shuhei; Shiodera, Taichiro; Takeguchi, Tomoyuki; Bannae, Shuhei; Kuhara, Shigehide

2018-03-13

Dynamic MR techniques, such as cardiac cine imaging, benefit from shorter acquisition times. The goal of the present study was to develop a method that achieves short acquisition times, while maintaining a cost-effective reconstruction, for dynamic MRI. k - t sensitivity encoding (SENSE) was identified as the base method to be enhanced meeting these two requirements. The proposed method achieves a reduction in acquisition time by estimating the spatiotemporal (x - f) sensitivity without requiring the acquisition of the alias-free signals, typical of the k - t SENSE technique. The cost-effective reconstruction, in turn, is achieved by a computationally efficient estimation of the x - f sensitivity from the band-limited signals of the aliased inputs. Such band-limited signals are suitable for sensitivity estimation because the strongly aliased signals have been removed. For the same reduction factor 4, the net reduction factor 4 for the proposed method was significantly higher than the factor 2.29 achieved by k - t SENSE. The processing time is reduced from 4.1 s for k - t SENSE to 1.7 s for the proposed method. The image quality obtained using the proposed method proved to be superior (mean squared error [MSE] ± standard deviation [SD] = 6.85 ± 2.73) compared to the k - t SENSE case (MSE ± SD = 12.73 ± 3.60) for the vertical long-axis (VLA) view, as well as other views. In the present study, k - t SENSE was identified as a suitable base method to be improved achieving both short acquisition times and a cost-effective reconstruction. To enhance these characteristics of base method, a novel implementation is proposed, estimating the x - f sensitivity without the need for an explicit scan of the reference signals. Experimental results showed that the acquisition, computational times and image quality for the proposed method were improved compared to the standard k - t SENSE method.

Optical imaging for the diagnosis of oral cancer and oral potentially malignant disorders

NASA Astrophysics Data System (ADS)

Yoshida, K.

2016-03-01

Optical Imaging is being conducted as a therapeutic non-invasive. Many kinds of the light source are selected for this purpose. Recently the oral cancer screening is conducted by using light-induced tissue autofluorescence examination such as several kinds of handheld devices. However, the mechanism of its action is still not clear. Therefore basic experimental research was conducted. One of auto fluorescence Imaging (AFI) device, VELscopeTM and near-infrared (NIR) fluorescence imaging using ICG-labeled antibody as a probe were compared using oral squamous cell carcinoma (OSCC) mouse models. The experiments revealed that intracutaneous tumor was successfully visualized as low density image by VELscopeTM and high density image by NIR image. In addition, VELscopeTM showed higher sensitivity and lower specificity than that of NIR fluorescence imaging and the sensitivity of identification of carcinoma areas with the VELscopeTM was good results. However, further more studies were needed to enhance the screening and diagnostic uses, sensitivity and specificity for detecting malignant lesions and differentiation from premalignant or benign lesions. Therefore, additional studies were conducted using a new developed near infrared (NIR) fluorescence imaging method targeting podoplanine (PDPN) which consists of indocyanine green (ICG)-labeled anti-human podoplanin antibody as a probe and IVIS imaging system or a handy realtime ICG imaging device that is overexpressed in oral malignant neoplasm to improve imaging for detection of early oral malignant neoplasm. Then evaluated for its sensitivity and specificity for detection of oral malignant neoplasm in xenografted mice model and compared with VELscopeTM. The results revealed that ICG fluorescence imaging method and VELscopeTM had the almost the same sensitivity for detection of oral malignant neoplasm. The current topics of optical imaging about oral malignant neoplasm were reviewed.

Polarization Sensitive Coherent Anti-Stokes Raman Spectroscopy of DCVJ in Doped Polymer

NASA Astrophysics Data System (ADS)

Ujj, Laszlo

2014-05-01

Coherent Raman Microscopy is an emerging technic and method to image biological samples such as living cells by recording vibrational fingerprints of molecules with high spatial resolution. The race is on to record the entire image during the shortest time possible in order to increase the time resolution of the recorded cellular events. The electronically enhanced polarization sensitive version of Coherent anti-Stokes Raman scattering is one of the method which can shorten the recording time and increase the sharpness of an image by enhancing the signal level of special molecular vibrational modes. In order to show the effectiveness of the method a model system, a highly fluorescence sample, DCVJ in a polymer matrix is investigated. Polarization sensitive resonance CARS spectra are recorded and analyzed. Vibrational signatures are extracted with model independent methods. Details of the measurements and data analysis will be presented. The author gratefully acknowledge the UWF for financial support.

The predictive value of magnetic resonance imaging of retinoblastoma for the likelihood of high-risk pathologic features.

PubMed

Hiasat, Jamila G; Saleh, Alaa; Al-Hussaini, Maysa; Al Nawaiseh, Ibrahim; Mehyar, Mustafa; Qandeel, Monther; Mohammad, Mona; Deebajah, Rasha; Sultan, Iyad; Jaradat, Imad; Mansour, Asem; Yousef, Yacoub A

2018-06-01

To evaluate the predictive value of magnetic resonance imaging in retinoblastoma for the likelihood of high-risk pathologic features. A retrospective study of 64 eyes enucleated from 60 retinoblastoma patients. Contrast-enhanced magnetic resonance imaging was performed before enucleation. Main outcome measures included demographics, laterality, accuracy, sensitivity, and specificity of magnetic resonance imaging in detecting high-risk pathologic features. Optic nerve invasion and choroidal invasion were seen microscopically in 34 (53%) and 28 (44%) eyes, respectively, while they were detected in magnetic resonance imaging in 22 (34%) and 15 (23%) eyes, respectively. The accuracy of magnetic resonance imaging in detecting prelaminar invasion was 77% (sensitivity 89%, specificity 98%), 56% for laminar invasion (sensitivity 27%, specificity 94%), 84% for postlaminar invasion (sensitivity 42%, specificity 98%), and 100% for optic cut edge invasion (sensitivity100%, specificity 100%). The accuracy of magnetic resonance imaging in detecting focal choroidal invasion was 48% (sensitivity 33%, specificity 97%), and 84% for massive choroidal invasion (sensitivity 53%, specificity 98%), and the accuracy in detecting extrascleral extension was 96% (sensitivity 67%, specificity 98%). Magnetic resonance imaging should not be the only method to stratify patients at high risk from those who are not, eventhough it can predict with high accuracy extensive postlaminar optic nerve invasion, massive choroidal invasion, and extrascleral tumor extension.

Application of image recognition-based automatic hyphae detection in fungal keratitis.

PubMed

Wu, Xuelian; Tao, Yuan; Qiu, Qingchen; Wu, Xinyi

2018-03-01

The purpose of this study is to evaluate the accuracy of two methods in diagnosis of fungal keratitis, whereby one method is automatic hyphae detection based on images recognition and the other method is corneal smear. We evaluate the sensitivity and specificity of the method in diagnosis of fungal keratitis, which is automatic hyphae detection based on image recognition. We analyze the consistency of clinical symptoms and the density of hyphae, and perform quantification using the method of automatic hyphae detection based on image recognition. In our study, 56 cases with fungal keratitis (just single eye) and 23 cases with bacterial keratitis were included. All cases underwent the routine inspection of slit lamp biomicroscopy, corneal smear examination, microorganism culture and the assessment of in vivo confocal microscopy images before starting medical treatment. Then, we recognize the hyphae images of in vivo confocal microscopy by using automatic hyphae detection based on image recognition to evaluate its sensitivity and specificity and compare with the method of corneal smear. The next step is to use the index of density to assess the severity of infection, and then find the correlation with the patients' clinical symptoms and evaluate consistency between them. The accuracy of this technology was superior to corneal smear examination (p < 0.05). The sensitivity of the technology of automatic hyphae detection of image recognition was 89.29%, and the specificity was 95.65%. The area under the ROC curve was 0.946. The correlation coefficient between the grading of the severity in the fungal keratitis by the automatic hyphae detection based on image recognition and the clinical grading is 0.87. The technology of automatic hyphae detection based on image recognition was with high sensitivity and specificity, able to identify fungal keratitis, which is better than the method of corneal smear examination. This technology has the advantages when compared with the conventional artificial identification of confocal microscope corneal images, of being accurate, stable and does not rely on human expertise. It was the most useful to the medical experts who are not familiar with fungal keratitis. The technology of automatic hyphae detection based on image recognition can quantify the hyphae density and grade this property. Being noninvasive, it can provide an evaluation criterion to fungal keratitis in a timely, accurate, objective and quantitative manner.

Simultaneous multi-headed imager geometry calibration method

DOEpatents

Tran, Vi-Hoa [Newport News, VA; Meikle, Steven Richard [Penshurst, AU; Smith, Mark Frederick [Yorktown, VA

2008-02-19

A method for calibrating multi-headed high sensitivity and high spatial resolution dynamic imaging systems, especially those useful in the acquisition of tomographic images of small animals. The method of the present invention comprises: simultaneously calibrating two or more detectors to the same coordinate system; and functionally correcting for unwanted detector movement due to gantry flexing.

A sub-sampled approach to extremely low-dose STEM

DOE PAGES

Stevens, A.; Luzi, L.; Yang, H.; ...

2018-01-22

The inpainting of deliberately and randomly sub-sampled images offers a potential means to image specimens at a high resolution and under extremely low-dose conditions (≤1 e -/Å 2) using a scanning transmission electron microscope. We show that deliberate sub-sampling acquires images at least an order of magnitude faster than conventional low-dose methods for an equivalent electron dose. More importantly, when adaptive sub-sampling is implemented to acquire the images, there is a significant increase in the resolution and sensitivity which accompanies the increase in imaging speed. Lastly, we demonstrate the potential of this method for beam sensitive materials and in-situ observationsmore » by experimentally imaging the node distribution in a metal-organic framework.« less

A sub-sampled approach to extremely low-dose STEM

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stevens, A.; Luzi, L.; Yang, H.

The inpainting of deliberately and randomly sub-sampled images offers a potential means to image specimens at a high resolution and under extremely low-dose conditions (≤1 e -/Å 2) using a scanning transmission electron microscope. We show that deliberate sub-sampling acquires images at least an order of magnitude faster than conventional low-dose methods for an equivalent electron dose. More importantly, when adaptive sub-sampling is implemented to acquire the images, there is a significant increase in the resolution and sensitivity which accompanies the increase in imaging speed. Lastly, we demonstrate the potential of this method for beam sensitive materials and in-situ observationsmore » by experimentally imaging the node distribution in a metal-organic framework.« less

A Sensitive TLRH Targeted Imaging Technique for Ultrasonic Molecular Imaging

PubMed Central

Hu, Xiaowen; Zheng, Hairong; Kruse, Dustin E.; Sutcliffe, Patrick; Stephens, Douglas N.; Ferrara, Katherine W.

2010-01-01

The primary goals of ultrasound molecular imaging are the detection and imaging of ultrasound contrast agents (microbubbles), which are bound to specific vascular surface receptors. Imaging methods that can sensitively and selectively detect and distinguish bound microbubbles from freely circulating microbubbles (free microbubbles) and surrounding tissue are critically important for the practical application of ultrasound contrast molecular imaging. Microbubbles excited by low frequency acoustic pulses emit wide-band echoes with a bandwidth extending beyond 20 MHz; we refer to this technique as TLRH (transmission at a low frequency and reception at a high frequency). Using this wideband, transient echo, we have developed and implemented a targeted imaging technique incorporating a multi-frequency co-linear array and the Siemens Antares® imaging system. The multi-frequency co-linear array integrates a center 5.4 MHz array, used to receive echoes and produce radiation force, and two outer 1.5 MHz arrays used to transmit low frequency incident pulses. The targeted imaging technique makes use of an acoustic radiation force sub-sequence to enhance accumulation and a TLRH imaging sub-sequence to detect bound microbubbles. The radiofrequency (RF) data obtained from the TLRH imaging sub-sequence are processsed to separate echo signatures between tissue, free microbubbles, and bound microbubbles. By imaging biotin-coated microbubbles targeted to avidin-coated cellulose tubes, we demonstrate that the proposed method has a high contrast-to-tissue ratio (up to 34 dB) and a high sensitivity to bound microbubbles (with the ratio of echoes from bound microbubbles versus free microbubbles extending up to 23 dB). The effects of the imaging pulse acoustic pressure, the radiation force sub-sequence and the use of various slow-time filters on the targeted imaging quality are studied. The TLRH targeted imaging method is demonstrated in this study to provide sensitive and selective detection of bound microbubbles for ultrasound molecularly-targeted imaging. PMID:20178897

Applying a 2D based CAD scheme for detecting micro-calcification clusters using digital breast tomosynthesis images: an assessment

NASA Astrophysics Data System (ADS)

Park, Sang Cheol; Zheng, Bin; Wang, Xiao-Hui; Gur, David

2008-03-01

Digital breast tomosynthesis (DBT) has emerged as a promising imaging modality for screening mammography. However, visually detecting micro-calcification clusters depicted on DBT images is a difficult task. Computer-aided detection (CAD) schemes for detecting micro-calcification clusters depicted on mammograms can achieve high performance and the use of CAD results can assist radiologists in detecting subtle micro-calcification clusters. In this study, we compared the performance of an available 2D based CAD scheme with one that includes a new grouping and scoring method when applied to both projection and reconstructed DBT images. We selected a dataset involving 96 DBT examinations acquired on 45 women. Each DBT image set included 11 low dose projection images and a varying number of reconstructed image slices ranging from 18 to 87. In this dataset 20 true-positive micro-calcification clusters were visually detected on the projection images and 40 were visually detected on the reconstructed images, respectively. We first applied the CAD scheme that was previously developed in our laboratory to the DBT dataset. We then tested a new grouping method that defines an independent cluster by grouping the same cluster detected on different projection or reconstructed images. We then compared four scoring methods to assess the CAD performance. The maximum sensitivity level observed for the different grouping and scoring methods were 70% and 88% for the projection and reconstructed images with a maximum false-positive rate of 4.0 and 15.9 per examination, respectively. This preliminary study demonstrates that (1) among the maximum, the minimum or the average CAD generated scores, using the maximum score of the grouped cluster regions achieved the highest performance level, (2) the histogram based scoring method is reasonably effective in reducing false-positive detections on the projection images but the overall CAD sensitivity is lower due to lower signal-to-noise ratio, and (3) CAD achieved higher sensitivity and higher false-positive rate (per examination) on the reconstructed images. We concluded that without changing the detection threshold or performing pre-filtering to possibly increase detection sensitivity, current CAD schemes developed and optimized for 2D mammograms perform relatively poorly and need to be re-optimized using DBT datasets and new grouping and scoring methods need to be incorporated into the schemes if these are to be used on the DBT examinations.

Phase sensitive optical coherence microscopy for photothermal imaging of gold nanorods

NASA Astrophysics Data System (ADS)

Hu, Yong; Podoleanu, Adrian G.; Dobre, George

2018-03-01

We describe a swept source based phase sensitive optical coherence microscopy (OCM) system for photothermal imaging of gold nanorods (GNR). The phase sensitive OCM system employed in the study has a displacement sensitivity of 0.17 nm to vibrations at single frequencies below 250 Hz. We demonstrate the generation of phase maps and confocal phase images. By displaying the difference between successive confocal phase images, we perform the confocal photothermal imaging of accumulated GNRs behind a glass coverslip and behind the scattering media separately. Compared with two-photon luminescence (TPL) detection techniques reported in literature, the technique in this study has the advantage of a simplified experimental setup and provides a more efficient method for imaging the aggregation of GNR. However, the repeatability performance of this technique suffers due to jitter noise from the swept laser source.

PH-sensitive fluorescence detection by diffuse fluorescence tomography

NASA Astrophysics Data System (ADS)

Li, Jiao; Gao, Feng; Duan, Linjing; Wang, Xin; Zhang, Limin; Zhao, Huijuan

2012-03-01

The importance of cellular pH has been shown clearly in the study of cell activity, pathological feature, drug metabolism, etc. Monitoring pH changes of living cells and imaging the regions with abnormal pH values in vivo could provide the physiologic and pathologic information for the research of the cell biology, pharmacokinetics, diagnostics and therapeutics of certain diseases such as cancer. Thus, pH-sensitive fluorescence imaging of bulk tissues has been attracting great attention in the regime of near-infrared diffuse fluorescence tomography (DFT), an efficient small-animal imaging tool. In this paper, the feasibility of quantifying pH-sensitive fluorescence targets in turbid medium is investigated using both time-domain and steady-state DFT methods. By use of the specifically designed time-domain and continuous-wave systems and the previously proposed image reconstruction scheme, we validate the method through 2-dimensional imaging experiments on a small-animal-sized phantom with multiply targets of distinct pH values. The results show that the approach can localize the targets with reasonable accuracy and achieve quantitative reconstruction of the pH-sensitive fluorescent yield.

Sensitivity enhancement of traveling wave MRI using free local resonators: an experimental demonstration.

PubMed

Zhang, Xiaoliang

2017-04-01

Traveling wave MR uses the far fields in signal excitation and reception, therefore its acquisition efficiency is low in contrast to the conventional near field magnetic resonance (MR). Here we show a simple and efficient method based on the local resonator to improving sensitivity of traveling wave MR technique. The proposed method utilizes a standalone or free local resonator to amplify the radio frequency magnetic fields in the interested target. The resonators have no wire connections to the MR system and thus can be conveniently placed to any place around imaging simples. A rectangular loop L/C resonator to be used as the free local resonator was tuned to the proton Larmor frequency at 7T. Traveling wave MR experiments with and without the wireless free local resonator were performed on a living rat using a 7T whole body MR scanner. The signal-to-noise ratio (SNR) or sensitivity of the images acquired was compared and evaluated. In vivo 7T imaging results show that traveling wave MR with a wireless free local resonator placed near the head of a living rat achieves at least 10-fold SNR gain over the images acquired on the same rat using conventional traveling wave MR method, i.e. imaging with no free local resonators. The proposed free local resonator technique is able to enhance the MR sensitivity and acquisition efficiency of traveling wave MR at ultrahigh fields in vivo . This method can be a simple solution to alleviating low sensitivity problem of traveling wave MRI.

Sensitivity and Specificity of Cardiac Tissue Discrimination Using Fiber-Optics Confocal Microscopy.

PubMed

Huang, Chao; Sachse, Frank B; Hitchcock, Robert W; Kaza, Aditya K

2016-01-01

Disturbances of the cardiac conduction system constitute a major risk after surgical repair of complex cases of congenital heart disease. Intraoperative identification of the conduction system may reduce the incidence of these disturbances. We previously developed an approach to identify cardiac tissue types using fiber-optics confocal microscopy and extracellular fluorophores. Here, we applied this approach to investigate sensitivity and specificity of human and automated classification in discriminating images of atrial working myocardium and specialized tissue of the conduction system. Two-dimensional image sequences from atrial working myocardium and nodal tissue of isolated perfused rodent hearts were acquired using a fiber-optics confocal microscope (Leica FCM1000). We compared two methods for local application of extracellular fluorophores: topical via pipette and with a dye carrier. Eight blinded examiners evaluated 162 randomly selected images of atrial working myocardium (n = 81) and nodal tissue (n = 81). In addition, we evaluated the images using automated classification. Blinded examiners achieved a sensitivity and specificity of 99.2 ± 0.3% and 98.0 ± 0.7%, respectively, with the dye carrier method of dye application. Sensitivity and specificity was similar for dye application via a pipette (99.2 ± 0.3% and 94.0 ± 2.4%, respectively). Sensitivity and specificity for automated methods of tissue discrimination were similarly high. Human and automated classification achieved high sensitivity and specificity in discriminating atrial working myocardium and nodal tissue. We suggest that our findings facilitate clinical translation of fiber-optics confocal microscopy as an intraoperative imaging modality to reduce the incidence of conduction disturbances during surgical correction of congenital heart disease.

Retina Image Vessel Segmentation Using a Hybrid CGLI Level Set Method

PubMed Central

Chen, Meizhu; Li, Jichun; Zhang, Encai

2017-01-01

As a nonintrusive method, the retina imaging provides us with a better way for the diagnosis of ophthalmologic diseases. Extracting the vessel profile automatically from the retina image is an important step in analyzing retina images. A novel hybrid active contour model is proposed to segment the fundus image automatically in this paper. It combines the signed pressure force function introduced by the Selective Binary and Gaussian Filtering Regularized Level Set (SBGFRLS) model with the local intensity property introduced by the Local Binary fitting (LBF) model to overcome the difficulty of the low contrast in segmentation process. It is more robust to the initial condition than the traditional methods and is easily implemented compared to the supervised vessel extraction methods. Proposed segmentation method was evaluated on two public datasets, DRIVE (Digital Retinal Images for Vessel Extraction) and STARE (Structured Analysis of the Retina) (the average accuracy of 0.9390 with 0.7358 sensitivity and 0.9680 specificity on DRIVE datasets and average accuracy of 0.9409 with 0.7449 sensitivity and 0.9690 specificity on STARE datasets). The experimental results show that our method is effective and our method is also robust to some kinds of pathology images compared with the traditional level set methods. PMID:28840122

A Set of Image Processing Algorithms for Computer-Aided Diagnosis in Nuclear Medicine Whole Body Bone Scan Images

NASA Astrophysics Data System (ADS)

Huang, Jia-Yann; Kao, Pan-Fu; Chen, Yung-Sheng

2007-06-01

Adjustment of brightness and contrast in nuclear medicine whole body bone scan images may confuse nuclear medicine physicians when identifying small bone lesions as well as making the identification of subtle bone lesion changes in sequential studies difficult. In this study, we developed a computer-aided diagnosis system, based on the fuzzy sets histogram thresholding method and anatomical knowledge-based image segmentation method that was able to analyze and quantify raw image data and identify the possible location of a lesion. To locate anatomical reference points, the fuzzy sets histogram thresholding method was adopted as a first processing stage to suppress the soft tissue in the bone images. Anatomical knowledge-based image segmentation method was then applied to segment the skeletal frame into different regions of homogeneous bones. For the different segmented bone regions, the lesion thresholds were set at different cut-offs. To obtain lesion thresholds in different segmented regions, the ranges and standard deviations of the image's gray-level distribution were obtained from 100 normal patients' whole body bone images and then, another 62 patients' images were used for testing. The two groups of images were independent. The sensitivity and the mean number of false lesions detected were used as performance indices to evaluate the proposed system. The overall sensitivity of the system is 92.1% (222 of 241) and 7.58 false detections per patient scan image. With a high sensitivity and an acceptable false lesions detection rate, this computer-aided automatic lesion detection system is demonstrated as useful and will probably in the future be able to help nuclear medicine physicians to identify possible bone lesions.

X-ray scatter imaging of hepatocellular carcinoma in a mouse model using nanoparticle contrast agents

DOE PAGES

Rand, Danielle; Derdak, Zoltan; Carlson, Rolf; ...

2015-10-29

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors worldwide and is almost uniformly fatal. Current methods of detection include ultrasound examination and imaging by CT scan or MRI; however, these techniques are problematic in terms of sensitivity and specificity, and the detection of early tumors (<1 cm diameter) has proven elusive. Better, more specific, and more sensitive detection methods are therefore urgently needed. Here we discuss the application of a newly developed x-ray imaging technique called Spatial Frequency Heterodyne Imaging (SFHI) for the early detection of HCC. SFHI uses x-rays scattered by an object to form anmore » image and is more sensitive than conventional absorption-based x-radiography. We show that tissues labeled in vivo with gold nanoparticle contrast agents can be detected using SFHI. We also demonstrate that directed targeting and SFHI of HCC tumors in a mouse model is possible through the use of HCC-specific antibodies. As a result, the enhanced sensitivity of SFHI relative to currently available techniques enables the x-ray imaging of tumors that are just a few millimeters in diameter and substantially reduces the amount of nanoparticle contrast agent required for intravenous injection relative to absorption-based x-ray imaging.« less

Design and characterization of planar capacitive imaging probe based on the measurement sensitivity distribution

NASA Astrophysics Data System (ADS)

Yin, X.; Chen, G.; Li, W.; Huthchins, D. A.

2013-01-01

Previous work indicated that the capacitive imaging (CI) technique is a useful NDE tool which can be used on a wide range of materials, including metals, glass/carbon fibre composite materials and concrete. The imaging performance of the CI technique for a given application is determined by design parameters and characteristics of the CI probe. In this paper, a rapid method for calculating the whole probe sensitivity distribution based on the finite element model (FEM) is presented to provide a direct view of the imaging capabilities of the planar CI probe. Sensitivity distributions of CI probes with different geometries were obtained. Influencing factors on sensitivity distribution were studied. Comparisons between CI probes with point-to-point triangular electrode pair and back-to-back triangular electrode pair were made based on the analysis of the corresponding sensitivity distributions. The results indicated that the sensitivity distribution could be useful for optimising the probe design parameters and predicting the imaging performance.

Low-cost polarization microscopy for cholesterol crystals

NASA Astrophysics Data System (ADS)

Kim, Kyungmin; Cho, Seonghee; Kim, Taehoon; Park, Hyoeun; Kim, Jinmoo; Lee, Seunghoon; Kang, Yeonsu; Chang, Kiyuk; Kim, Chulhong

2018-02-01

Because cholesterol crystals (Chcs) are a major cause of atherosclerosis, imaging Chcs in tissues with high sensitivity and specificity is important in diagnosing and predicting atherosclerosis. Polarizing microscopy (PM) has been widely used to image crystalline materials in tissues, but it has been difficult to distinguish Chcs from other crystalline materials in tissues. Thus, various methods such as fluorescent dye staining, Raman spectroscopy, and two-photon microscopy (TPM) have been developed to image Chcs with high sensitivity and specificity. However, these methods require expensive equipment or complex processes. Therefore, we have developed a low-cost, easy-to-use PM system using an LED light source that can distinguish Chcs from other crystalline materials with high sensitivity and specificity. Due to the nature of the LED spectrum in our system, collagen is displayed in yellow and Chcs in blue. In addition, we have improved the sensitivity and specificity by creating an aqueous condition on the sample. In the aqueous state, signals of yellowish collagen fibers were reduced and signals of Chcs were highlighted. The Chcs detection capability of our system was verified compared with the TPM image. In addition, clinical feasibility was shown by comparison with existing histological methods.

Coronary angiography using synchrotron radiation (invited)

NASA Astrophysics Data System (ADS)

Thompson, A. C.; Rubenstein, E.; Zeman, H. D.; Hofstadter, R.; Otis, J. N.; Giacomini, J. C.; Gordon, H. J.; Brown, G. S.; Thomlinson, W.; Kernoff, R. S.

1989-07-01

Imaging of coronary arteries using a venous instead of an arterial injection of contrast agent could provide a much safer method to diagnose heart disease. The tunability, intensity, and collimation of synchrotron radiation x-ray beams makes possible imaging systems with greatly improved imaging sensitivity. A pair of fan x-ray beams, a movable patient chair, and a multielement x-ray detector are used to acquire a pair of x-ray images above and below the iodine K edge. The logarithmic subtraction of these two images produces an image with excellent sensitivity to contrast agent and minimal sensitivity to bone and tissue. High-quality images from a dog and preliminary images from five humans have been obtained. Improvements are being made to the system to increase the effective radiation flux and to measure the position of both x-ray beams.

Automated image alignment and segmentation to follow progression of geographic atrophy in age-related macular degeneration.

PubMed

Ramsey, David J; Sunness, Janet S; Malviya, Poorva; Applegate, Carol; Hager, Gregory D; Handa, James T

2014-07-01

To develop a computer-based image segmentation method for standardizing the quantification of geographic atrophy (GA). The authors present an automated image segmentation method based on the fuzzy c-means clustering algorithm for the detection of GA lesions. The method is evaluated by comparing computerized segmentation against outlines of GA drawn by an expert grader for a longitudinal series of fundus autofluorescence images with paired 30° color fundus photographs for 10 patients. The automated segmentation method showed excellent agreement with an expert grader for fundus autofluorescence images, achieving a performance level of 94 ± 5% sensitivity and 98 ± 2% specificity on a per-pixel basis for the detection of GA area, but performed less well on color fundus photographs with a sensitivity of 47 ± 26% and specificity of 98 ± 2%. The segmentation algorithm identified 75 ± 16% of the GA border correctly in fundus autofluorescence images compared with just 42 ± 25% for color fundus photographs. The results of this study demonstrate a promising computerized segmentation method that may enhance the reproducibility of GA measurement and provide an objective strategy to assist an expert in the grading of images.

Patient-Adaptive Reconstruction and Acquisition in Dynamic Imaging with Sensitivity Encoding (PARADISE)

PubMed Central

Sharif, Behzad; Derbyshire, J. Andrew; Faranesh, Anthony Z.; Bresler, Yoram

2010-01-01

MR imaging of the human heart without explicit cardiac synchronization promises to extend the applicability of cardiac MR to a larger patient population and potentially expand its diagnostic capabilities. However, conventional non-gated imaging techniques typically suffer from low image quality or inadequate spatio-temporal resolution and fidelity. Patient-Adaptive Reconstruction and Acquisition in Dynamic Imaging with Sensitivity Encoding (PARADISE) is a highly-accelerated non-gated dynamic imaging method that enables artifact-free imaging with high spatio-temporal resolutions by utilizing novel computational techniques to optimize the imaging process. In addition to using parallel imaging, the method gains acceleration from a physiologically-driven spatio-temporal support model; hence, it is doubly accelerated. The support model is patient-adaptive, i.e., its geometry depends on dynamics of the imaged slice, e.g., subject’s heart-rate and heart location within the slice. The proposed method is also doubly adaptive as it adapts both the acquisition and reconstruction schemes. Based on the theory of time-sequential sampling, the proposed framework explicitly accounts for speed limitations of gradient encoding and provides performance guarantees on achievable image quality. The presented in-vivo results demonstrate the effectiveness and feasibility of the PARADISE method for high resolution non-gated cardiac MRI during a short breath-hold. PMID:20665794

A simplified implementation of edge detection in MATLAB is faster and more sensitive than fast fourier transform for actin fiber alignment quantification.

PubMed

Kemeny, Steven Frank; Clyne, Alisa Morss

2011-04-01

Fiber alignment plays a critical role in the structure and function of cells and tissues. While fiber alignment quantification is important to experimental analysis and several different methods for quantifying fiber alignment exist, many studies focus on qualitative rather than quantitative analysis perhaps due to the complexity of current fiber alignment methods. Speed and sensitivity were compared in edge detection and fast Fourier transform (FFT) for measuring actin fiber alignment in cells exposed to shear stress. While edge detection using matrix multiplication was consistently more sensitive than FFT, image processing time was significantly longer. However, when MATLAB functions were used to implement edge detection, MATLAB's efficient element-by-element calculations and fast filtering techniques reduced computation cost 100 times compared to the matrix multiplication edge detection method. The new computation time was comparable to the FFT method, and MATLAB edge detection produced well-distributed fiber angle distributions that statistically distinguished aligned and unaligned fibers in half as many sample images. When the FFT sensitivity was improved by dividing images into smaller subsections, processing time grew larger than the time required for MATLAB edge detection. Implementation of edge detection in MATLAB is simpler, faster, and more sensitive than FFT for fiber alignment quantification.

Flip-flop method: A new T1-weighted flow-MRI for plants studies.

PubMed

Buy, Simon; Le Floch, Simon; Tang, Ning; Sidiboulenouar, Rahima; Zanca, Michel; Canadas, Patrick; Nativel, Eric; Cardoso, Maida; Alibert, Eric; Dupont, Guillaume; Ambard, Dominique; Maurel, Christophe; Verdeil, Jean-Luc; Bertin, Nadia; Goze-Bac, Christophe; Coillot, Christophe

2018-01-01

The climate warming implies an increase of stress of plants (drought and torrential rainfall). The understanding of plant behavior, in this context, takes a major importance and sap flow measurement in plants remains a key issue for plant understanding. Magnetic Resonance Imaging (MRI) which is well known to be a powerful tool to access water quantity can be used to measure moving water. We describe a novel flow-MRI method which takes advantage of inflow slice sensitivity. The method involves the slice selectivity in the context of multi slice spin echo sequence. Two sequences such as a given slice is consecutively inflow and outflow sensitive are performed, offering the possiblility to perform slow flow sensitive imaging in a quite straigthforward way. The method potential is demonstrated by imaging both a slow flow measurement on a test bench (as low as 10 μm.s-1) and the Poiseuille's profile of xylemian sap flow velocity in the xylematic tissues of a tomato plant stem.

Label-free imaging and spectroscopy for early detection of cervical cancer.

PubMed

Jing, Yueyue; Wang, Yulan; Wang, Xinyi; Song, Chuan; Ma, Jiong; Xie, Yonghui; Fei, Yiyan; Zhang, Qinghua; Mi, Lan

2018-05-01

The label-free imaging and spectroscopy method was studied on cervical unstained tissue sections obtained from 36 patients. The native fluorescence spectra of tissues are analyzed by the optical redox ratio (ORR), which is defined as fluorescence intensity ratio between NADH and FAD, and indicates the metabolism change with the cancer development. The ORRs of normal tissues are consistently higher than those of precancer or cancerous tissues. A criterion line of ORR at 5.0 can be used to discriminate cervical precancer/cancer from normal tissues. The sensitivity and specificity of the native fluorescence spectroscopy method for cervical cancer diagnosis are determined as 100% and 91%. Moreover, the native fluorescence spectroscopy study is much more sensitive on the healthy region of cervical precancer/cancer patients compared with the traditional clinical staining method. The results suggest label-free imaging and spectroscopy is a fast, highly sensitive and specific method on the detection of cervical cancer. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A Novel Bit-level Image Encryption Method Based on Chaotic Map and Dynamic Grouping

NASA Astrophysics Data System (ADS)

Zhang, Guo-Ji; Shen, Yan

2012-10-01

In this paper, a novel bit-level image encryption method based on dynamic grouping is proposed. In the proposed method, the plain-image is divided into several groups randomly, then permutation-diffusion process on bit level is carried out. The keystream generated by logistic map is related to the plain-image, which confuses the relationship between the plain-image and the cipher-image. The computer simulation results of statistical analysis, information entropy analysis and sensitivity analysis show that the proposed encryption method is secure and reliable enough to be used for communication application.

Validation of various adaptive threshold methods of segmentation applied to follicular lymphoma digital images stained with 3,3’-Diaminobenzidine&Haematoxylin

PubMed Central

2013-01-01

The comparative study of the results of various segmentation methods for the digital images of the follicular lymphoma cancer tissue section is described in this paper. The sensitivity and specificity and some other parameters of the following adaptive threshold methods of segmentation: the Niblack method, the Sauvola method, the White method, the Bernsen method, the Yasuda method and the Palumbo method, are calculated. Methods are applied to three types of images constructed by extraction of the brown colour information from the artificial images synthesized based on counterpart experimentally captured images. This paper presents usefulness of the microscopic image synthesis method in evaluation as well as comparison of the image processing results. The results of thoughtful analysis of broad range of adaptive threshold methods applied to: (1) the blue channel of RGB, (2) the brown colour extracted by deconvolution and (3) the ’brown component’ extracted from RGB allows to select some pairs: method and type of image for which this method is most efficient considering various criteria e.g. accuracy and precision in area detection or accuracy in number of objects detection and so on. The comparison shows that the White, the Bernsen and the Sauvola methods results are better than the results of the rest of the methods for all types of monochromatic images. All three methods segments the immunopositive nuclei with the mean accuracy of 0.9952, 0.9942 and 0.9944 respectively, when treated totally. However the best results are achieved for monochromatic image in which intensity shows brown colour map constructed by colour deconvolution algorithm. The specificity in the cases of the Bernsen and the White methods is 1 and sensitivities are: 0.74 for White and 0.91 for Bernsen methods while the Sauvola method achieves sensitivity value of 0.74 and the specificity value of 0.99. According to Bland-Altman plot the Sauvola method selected objects are segmented without undercutting the area for true positive objects but with extra false positive objects. The Sauvola and the Bernsen methods gives complementary results what will be exploited when the new method of virtual tissue slides segmentation be develop. Virtual Slides The virtual slides for this article can be found here: slide 1: http://diagnosticpathology.slidepath.com/dih/webViewer.php?snapshotId=13617947952577 and slide 2: http://diagnosticpathology.slidepath.com/dih/webViewer.php?snapshotId=13617948230017. PMID:23531405

Validation of various adaptive threshold methods of segmentation applied to follicular lymphoma digital images stained with 3,3'-Diaminobenzidine&Haematoxylin.

PubMed

Korzynska, Anna; Roszkowiak, Lukasz; Lopez, Carlos; Bosch, Ramon; Witkowski, Lukasz; Lejeune, Marylene

2013-03-25

The comparative study of the results of various segmentation methods for the digital images of the follicular lymphoma cancer tissue section is described in this paper. The sensitivity and specificity and some other parameters of the following adaptive threshold methods of segmentation: the Niblack method, the Sauvola method, the White method, the Bernsen method, the Yasuda method and the Palumbo method, are calculated. Methods are applied to three types of images constructed by extraction of the brown colour information from the artificial images synthesized based on counterpart experimentally captured images. This paper presents usefulness of the microscopic image synthesis method in evaluation as well as comparison of the image processing results. The results of thoughtful analysis of broad range of adaptive threshold methods applied to: (1) the blue channel of RGB, (2) the brown colour extracted by deconvolution and (3) the 'brown component' extracted from RGB allows to select some pairs: method and type of image for which this method is most efficient considering various criteria e.g. accuracy and precision in area detection or accuracy in number of objects detection and so on. The comparison shows that the White, the Bernsen and the Sauvola methods results are better than the results of the rest of the methods for all types of monochromatic images. All three methods segments the immunopositive nuclei with the mean accuracy of 0.9952, 0.9942 and 0.9944 respectively, when treated totally. However the best results are achieved for monochromatic image in which intensity shows brown colour map constructed by colour deconvolution algorithm. The specificity in the cases of the Bernsen and the White methods is 1 and sensitivities are: 0.74 for White and 0.91 for Bernsen methods while the Sauvola method achieves sensitivity value of 0.74 and the specificity value of 0.99. According to Bland-Altman plot the Sauvola method selected objects are segmented without undercutting the area for true positive objects but with extra false positive objects. The Sauvola and the Bernsen methods gives complementary results what will be exploited when the new method of virtual tissue slides segmentation be develop. The virtual slides for this article can be found here: slide 1: http://diagnosticpathology.slidepath.com/dih/webViewer.php?snapshotId=13617947952577 and slide 2: http://diagnosticpathology.slidepath.com/dih/webViewer.php?snapshotId=13617948230017.

Imaging Human Brain Perfusion with Inhaled Hyperpolarized 129Xe MR Imaging.

PubMed

Rao, Madhwesha R; Stewart, Neil J; Griffiths, Paul D; Norquay, Graham; Wild, Jim M

2018-02-01

Purpose To evaluate the feasibility of directly imaging perfusion of human brain tissue by using magnetic resonance (MR) imaging with inhaled hyperpolarized xenon 129 ( 129 Xe). Materials and Methods In vivo imaging with 129 Xe was performed in three healthy participants. The combination of a high-yield spin-exchange optical pumping 129 Xe polarizer, custom-built radiofrequency coils, and an optimized gradient-echo MR imaging protocol was used to achieve signal sensitivity sufficient to directly image hyperpolarized 129 Xe dissolved in the human brain. Conventional T1-weighted proton (hydrogen 1 [ 1 H]) images and perfusion images by using arterial spin labeling were obtained for comparison. Results Images of 129 Xe uptake were obtained with a signal-to-noise ratio of 31 ± 9 and demonstrated structural similarities to the gray matter distribution on conventional T1-weighted 1 H images and to perfusion images from arterial spin labeling. Conclusion Hyperpolarized 129 Xe MR imaging is an injection-free means of imaging the perfusion of cerebral tissue. The proposed method images the uptake of inhaled xenon gas to the extravascular brain tissue compartment across the intact blood-brain barrier. This level of sensitivity is not readily available with contemporary MR imaging methods. © RSNA, 2017.

Resolution experiments using the white light speckle method.

PubMed

Conley, E; Cloud, G

1991-03-01

Noncoherent light speckle methods have been successfully applied to gauge the motion of glaciers and buildings. Resolution of the optical method was limited by the aberrating turbulent atmosphere through which the images were collected. Sensitivity limitations regarding this particular application of speckle interferometry are discussed and analyzed. Resolution limit experiments that were incidental to glacier flow studies are related to the basic theory of astronomical imaging. Optical resolution of the ice flow measurement technique is shown to be in substantial agreement with the sensitivity predictions of astronomy theory.

Study of a non-diffusing radiochromic gel dosimeter for 3D radiation dose imaging

NASA Astrophysics Data System (ADS)

Marsden, Craig Michael

2000-12-01

This thesis investigates the potential of a new radiation gel dosimeter, based on nitro-blue tetrazolium (NBTZ) suspended in a gelatin mold. Unlike all Fricke based gel dosimeters this dosimeter does not suffer from diffusive loss of image stability. Images are obtained by an optical tomography method. Nitro blue tetrazolium is a common biological indicator that when irradiated in an aqueous medium undergoes reduction to a highly colored formazan, which has an absorbance maximum at 525nm. Tetrazolium is water soluble while the formazan product is insoluble. The formazan product sticks to the gelatin matrix and the dose image is maintained for three months. Methods to maximize the sensitivity of the system were evaluated. It was found that a chemical detergent, Triton X-100, in combination with sodium formate, increased the dosimeter sensitivity significantly. An initial G-value of formazan production for a dosimeter composed of 1mM NBTZ, gelatin, and water was on the order of 0.2. The addition of Triton and formate produced a G-value in excess of 5.0. The effects of NBTZ, triton, formate, and gel concentration were all investigated. All the gels provided linear dose vs. absorbance plots for doses from 0 to >100 Gy. It was determined that gel concentration had minimal if any effect on sensitivity. Sensitivity increased slightly with increasing NBTZ concentration. Triton and formate individually and together provided moderate to large increases in dosimeter sensitivity. The dosimeter described in this work can provide stable 3D radiation dose images for all modalities of radiation therapy equipment. Methods to increase sensitivity are developed and discussed.

Ultrahigh sensitive optical microangiography reveals depth-resolved microcirculation and its longitudinal response to prolonged ischemic event within skeletal muscles in mice

NASA Astrophysics Data System (ADS)

Jia, Yali; Qin, Jia; Zhi, Zhongwei; Wang, Ruikang K.

2011-08-01

The primary pathophysiology of peripheral arterial disease is associated with impaired perfusion to the muscle tissue in the lower extremities. The lack of effective pharmacologic treatments that stimulate vessel collateralization emphasizes the need for an imaging method that can be used to dynamically visualize depth-resolved microcirculation within muscle tissues. Optical microangiography (OMAG) is a recently developed label-free imaging method capable of producing three-dimensional images of dynamic blood perfusion within microcirculatory tissue beds at an imaging depth of up to ~2 mm, with an unprecedented imaging sensitivity of blood flow at ~4 μm/s. In this paper, we demonstrate the utility of OMAG in imaging the detailed blood flow distributions, at a capillary-level resolution, within skeletal muscles of mice. By use of the mouse model of hind-limb ischemia, we show that OMAG can assess the time-dependent changes in muscle perfusion and perfusion restoration along tissue depth. These findings indicate that OMAG can represent a sensitive, consistent technique to effectively study pharmacologic therapies aimed at promoting the growth and development of collateral vessels.

Research on the shortwave infrared hyperspectral imaging technology based on Integrated Stepwise filter

NASA Astrophysics Data System (ADS)

Wei, Liqing; Xiao, Xizhong; Wang, Yueming; Zhuang, Xiaoqiong; Wang, Jianyu

2017-11-01

Space-borne hyperspectral imagery is an important tool for earth sciences and industrial applications. Higher spatial and spectral resolutions have been sought persistently, although this results in more power, larger volume and weight during a space-borne spectral imager design. For miniaturization of hyperspectral imager and optimization of spectral splitting methods, several methods are compared in this paper. Spectral time delay integration (TDI) method with high transmittance Integrated Stepwise Filter (ISF) is proposed.With the method, an ISF imaging spectrometer with TDI could achieve higher system sensitivity than the traditional prism/grating imaging spectrometer. In addition, the ISF imaging spectrometer performs well in suppressing infrared background radiation produced by instrument. A compact shortwave infrared (SWIR) hyperspectral imager prototype based on HgCdTe covering the spectral range of 2.0-2.5 μm with 6 TDI stages was designed and integrated. To investigate the performance of ISF spectrometer, a method to derive the optimal blocking band curve of the ISF is introduced, along with known error characteristics. To assess spectral performance of the ISF system, a new spectral calibration based on blackbody radiation with temperature scanning is proposed. The results of the imaging experiment showed the merits of ISF. ISF has great application prospects in the field of high sensitivity and high resolution space-borne hyperspectral imagery.

Near-infrared fluorescence image quality test methods for standardized performance evaluation

NASA Astrophysics Data System (ADS)

Kanniyappan, Udayakumar; Wang, Bohan; Yang, Charles; Ghassemi, Pejhman; Wang, Quanzeng; Chen, Yu; Pfefer, Joshua

2017-03-01

Near-infrared fluorescence (NIRF) imaging has gained much attention as a clinical method for enhancing visualization of cancers, perfusion and biological structures in surgical applications where a fluorescent dye is monitored by an imaging system. In order to address the emerging need for standardization of this innovative technology, it is necessary to develop and validate test methods suitable for objective, quantitative assessment of device performance. Towards this goal, we develop target-based test methods and investigate best practices for key NIRF imaging system performance characteristics including spatial resolution, depth of field and sensitivity. Characterization of fluorescence properties was performed by generating excitation-emission matrix properties of indocyanine green and quantum dots in biological solutions and matrix materials. A turbid, fluorophore-doped target was used, along with a resolution target for assessing image sharpness. Multi-well plates filled with either liquid or solid targets were generated to explore best practices for evaluating detection sensitivity. Overall, our results demonstrate the utility of objective, quantitative, target-based testing approaches as well as the need to consider a wide range of factors in establishing standardized approaches for NIRF imaging system performance.

Label-free in vivo optical micro-angiography imaging of cerebral capillary blood flow within meninges and cortex in mice with the skull left intact

NASA Astrophysics Data System (ADS)

Jia, Yali; Wang, Ruikang K.

2011-03-01

Abnormal microcirculation within meninges is common in many neurological diseases. There is a need for an imaging method that is capable of visualizing functional meningeal microcirculations alone, preferably decoupled from the cortical blood flow. Optical microangiography (OMAG) is a recently developed label-free imaging method capable of producing 3D images of dynamic blood perfusion within micro-circulatory tissue beds at an imaging depth up to ~2 mm, with an unprecedented imaging sensitivity to the blood flow at ~4 μm/s. In this study, we demonstrate the utility of ultra-high sensitive OMAG in imaging the detailed blood flow distributions, at a capillary level resolution, within meninges and cortex in mice with the cranium left intact. The results indicate that OMAG can be a valuable tool for the study of meningeal circulations.

Automated detection of pulmonary nodules in PET/CT images: Ensemble false-positive reduction using a convolutional neural network technique

DOE Office of Scientific and Technical Information (OSTI.GOV)

Teramoto, Atsushi, E-mail: teramoto@fujita-hu.ac.jp; Fujita, Hiroshi; Yamamuro, Osamu

Purpose: Automated detection of solitary pulmonary nodules using positron emission tomography (PET) and computed tomography (CT) images shows good sensitivity; however, it is difficult to detect nodules in contact with normal organs, and additional efforts are needed so that the number of false positives (FPs) can be further reduced. In this paper, the authors propose an improved FP-reduction method for the detection of pulmonary nodules in PET/CT images by means of convolutional neural networks (CNNs). Methods: The overall scheme detects pulmonary nodules using both CT and PET images. In the CT images, a massive region is first detected using anmore » active contour filter, which is a type of contrast enhancement filter that has a deformable kernel shape. Subsequently, high-uptake regions detected by the PET images are merged with the regions detected by the CT images. FP candidates are eliminated using an ensemble method; it consists of two feature extractions, one by shape/metabolic feature analysis and the other by a CNN, followed by a two-step classifier, one step being rule based and the other being based on support vector machines. Results: The authors evaluated the detection performance using 104 PET/CT images collected by a cancer-screening program. The sensitivity in detecting candidates at an initial stage was 97.2%, with 72.8 FPs/case. After performing the proposed FP-reduction method, the sensitivity of detection was 90.1%, with 4.9 FPs/case; the proposed method eliminated approximately half the FPs existing in the previous study. Conclusions: An improved FP-reduction scheme using CNN technique has been developed for the detection of pulmonary nodules in PET/CT images. The authors’ ensemble FP-reduction method eliminated 93% of the FPs; their proposed method using CNN technique eliminates approximately half the FPs existing in the previous study. These results indicate that their method may be useful in the computer-aided detection of pulmonary nodules using PET/CT images.« less

Improved spatial regression analysis of diffusion tensor imaging for lesion detection during longitudinal progression of multiple sclerosis in individual subjects

NASA Astrophysics Data System (ADS)

Liu, Bilan; Qiu, Xing; Zhu, Tong; Tian, Wei; Hu, Rui; Ekholm, Sven; Schifitto, Giovanni; Zhong, Jianhui

2016-03-01

Subject-specific longitudinal DTI study is vital for investigation of pathological changes of lesions and disease evolution. Spatial Regression Analysis of Diffusion tensor imaging (SPREAD) is a non-parametric permutation-based statistical framework that combines spatial regression and resampling techniques to achieve effective detection of localized longitudinal diffusion changes within the whole brain at individual level without a priori hypotheses. However, boundary blurring and dislocation limit its sensitivity, especially towards detecting lesions of irregular shapes. In the present study, we propose an improved SPREAD (dubbed improved SPREAD, or iSPREAD) method by incorporating a three-dimensional (3D) nonlinear anisotropic diffusion filtering method, which provides edge-preserving image smoothing through a nonlinear scale space approach. The statistical inference based on iSPREAD was evaluated and compared with the original SPREAD method using both simulated and in vivo human brain data. Results demonstrated that the sensitivity and accuracy of the SPREAD method has been improved substantially by adapting nonlinear anisotropic filtering. iSPREAD identifies subject-specific longitudinal changes in the brain with improved sensitivity, accuracy, and enhanced statistical power, especially when the spatial correlation is heterogeneous among neighboring image pixels in DTI.

A Real-Time Near-Infrared Fluorescence Imaging Method for the Detection of Oral Cancers in Mice Using an Indocyanine Green-Labeled Podoplanin Antibody.

PubMed

Ito, Akihiro; Ohta, Mitsuhiko; Kato, Yukinari; Inada, Shunko; Kato, Toshio; Nakata, Susumu; Yatabe, Yasushi; Goto, Mitsuo; Kaneda, Norio; Kurita, Kenichi; Nakanishi, Hayao; Yoshida, Kenji

2018-01-01

Podoplanin is distinctively overexpressed in oral squamous cell carcinoma than oral benign neoplasms and plays a crucial role in the pathogenesis and metastasis of oral squamous cell carcinoma but its diagnostic application is quite limited. Here, we report a new near-infrared fluorescence imaging method using an indocyanine green (ICG)-labeled anti-podoplanin antibody and a desktop/a handheld ICG detection device for the visualization of oral squamous cell carcinoma-xenografted tumors in nude mice. Both near-infrared imaging methods using a desktop (in vivo imaging system: IVIS) and a handheld device (photodynamic eye: PDE) successfully detected oral squamous cell carcinoma tumors in nude mice in a podoplanin expression-dependent manner with comparable sensitivity. Of these 2 devices, only near-infrared imaging methods using a handheld device visualized oral squamous cell carcinoma xenografts in mice in real time. Furthermore, near-infrared imaging methods using the handheld device (PDE) could detect smaller podoplanin-positive oral squamous cell carcinoma tumors than a non-near-infrared, autofluorescence-based imaging method. Based on these results, a near-infrared imaging method using an ICG-labeled anti-podoplanin antibody and a handheld detection device (PDE) allows the sensitive, semiquantitative, and real-time imaging of oral squamous cell carcinoma tumors and therefore represents a useful tool for the detection and subsequent monitoring of malignant oral neoplasms in both preclinical and some clinical settings.

A Real-Time Near-Infrared Fluorescence Imaging Method for the Detection of Oral Cancers in Mice Using an Indocyanine Green–Labeled Podoplanin Antibody

PubMed Central

Ito, Akihiro; Ohta, Mitsuhiko; Kato, Yukinari; Inada, Shunko; Kato, Toshio; Nakata, Susumu; Yatabe, Yasushi; Goto, Mitsuo; Kaneda, Norio; Kurita, Kenichi; Nakanishi, Hayao; Yoshida, Kenji

2018-01-01

Podoplanin is distinctively overexpressed in oral squamous cell carcinoma than oral benign neoplasms and plays a crucial role in the pathogenesis and metastasis of oral squamous cell carcinoma but its diagnostic application is quite limited. Here, we report a new near-infrared fluorescence imaging method using an indocyanine green (ICG)–labeled anti-podoplanin antibody and a desktop/a handheld ICG detection device for the visualization of oral squamous cell carcinoma–xenografted tumors in nude mice. Both near-infrared imaging methods using a desktop (in vivo imaging system: IVIS) and a handheld device (photodynamic eye: PDE) successfully detected oral squamous cell carcinoma tumors in nude mice in a podoplanin expression–dependent manner with comparable sensitivity. Of these 2 devices, only near-infrared imaging methods using a handheld device visualized oral squamous cell carcinoma xenografts in mice in real time. Furthermore, near-infrared imaging methods using the handheld device (PDE) could detect smaller podoplanin-positive oral squamous cell carcinoma tumors than a non-near-infrared, autofluorescence-based imaging method. Based on these results, a near-infrared imaging method using an ICG-labeled anti-podoplanin antibody and a handheld detection device (PDE) allows the sensitive, semiquantitative, and real-time imaging of oral squamous cell carcinoma tumors and therefore represents a useful tool for the detection and subsequent monitoring of malignant oral neoplasms in both preclinical and some clinical settings. PMID:29649929

Detection of blob objects in microscopic zebrafish images based on gradient vector diffusion.

PubMed

Li, Gang; Liu, Tianming; Nie, Jingxin; Guo, Lei; Malicki, Jarema; Mara, Andrew; Holley, Scott A; Xia, Weiming; Wong, Stephen T C

2007-10-01

The zebrafish has become an important vertebrate animal model for the study of developmental biology, functional genomics, and disease mechanisms. It is also being used for drug discovery. Computerized detection of blob objects has been one of the important tasks in quantitative phenotyping of zebrafish. We present a new automated method that is able to detect blob objects, such as nuclei or cells in microscopic zebrafish images. This method is composed of three key steps. The first step is to produce a diffused gradient vector field by a physical elastic deformable model. In the second step, the flux image is computed on the diffused gradient vector field. The third step performs thresholding and nonmaximum suppression based on the flux image. We report the validation and experimental results of this method using zebrafish image datasets from three independent research labs. Both sensitivity and specificity of this method are over 90%. This method is able to differentiate closely juxtaposed or connected blob objects, with high sensitivity and specificity in different situations. It is characterized by a good, consistent performance in blob object detection.

Image Reconstruction for a Partially Collimated Whole Body PET Scanner

PubMed Central

Alessio, Adam M.; Schmitz, Ruth E.; MacDonald, Lawrence R.; Wollenweber, Scott D.; Stearns, Charles W.; Ross, Steven G.; Ganin, Alex; Lewellen, Thomas K.; Kinahan, Paul E.

2008-01-01

Partially collimated PET systems have less collimation than conventional 2-D systems and have been shown to offer count rate improvements over 2-D and 3-D systems. Despite this potential, previous efforts have not established image-based improvements with partial collimation and have not customized the reconstruction method for partially collimated data. This work presents an image reconstruction method tailored for partially collimated data. Simulated and measured sensitivity patterns are presented and provide a basis for modification of a fully 3-D reconstruction technique. The proposed method uses a measured normalization correction term to account for the unique sensitivity to true events. This work also proposes a modified scatter correction based on simulated data. Measured image quality data supports the use of the normalization correction term for true events, and suggests that the modified scatter correction is unnecessary. PMID:19096731

Image Reconstruction for a Partially Collimated Whole Body PET Scanner.

PubMed

Alessio, Adam M; Schmitz, Ruth E; Macdonald, Lawrence R; Wollenweber, Scott D; Stearns, Charles W; Ross, Steven G; Ganin, Alex; Lewellen, Thomas K; Kinahan, Paul E

2008-06-01

Partially collimated PET systems have less collimation than conventional 2-D systems and have been shown to offer count rate improvements over 2-D and 3-D systems. Despite this potential, previous efforts have not established image-based improvements with partial collimation and have not customized the reconstruction method for partially collimated data. This work presents an image reconstruction method tailored for partially collimated data. Simulated and measured sensitivity patterns are presented and provide a basis for modification of a fully 3-D reconstruction technique. The proposed method uses a measured normalization correction term to account for the unique sensitivity to true events. This work also proposes a modified scatter correction based on simulated data. Measured image quality data supports the use of the normalization correction term for true events, and suggests that the modified scatter correction is unnecessary.

Automated and unsupervised detection of malarial parasites in microscopic images.

PubMed

Purwar, Yashasvi; Shah, Sirish L; Clarke, Gwen; Almugairi, Areej; Muehlenbachs, Atis

2011-12-13

Malaria is a serious infectious disease. According to the World Health Organization, it is responsible for nearly one million deaths each year. There are various techniques to diagnose malaria of which manual microscopy is considered to be the gold standard. However due to the number of steps required in manual assessment, this diagnostic method is time consuming (leading to late diagnosis) and prone to human error (leading to erroneous diagnosis), even in experienced hands. The focus of this study is to develop a robust, unsupervised and sensitive malaria screening technique with low material cost and one that has an advantage over other techniques in that it minimizes human reliance and is, therefore, more consistent in applying diagnostic criteria. A method based on digital image processing of Giemsa-stained thin smear image is developed to facilitate the diagnostic process. The diagnosis procedure is divided into two parts; enumeration and identification. The image-based method presented here is designed to automate the process of enumeration and identification; with the main advantage being its ability to carry out the diagnosis in an unsupervised manner and yet have high sensitivity and thus reducing cases of false negatives. The image based method is tested over more than 500 images from two independent laboratories. The aim is to distinguish between positive and negative cases of malaria using thin smear blood slide images. Due to the unsupervised nature of method it requires minimal human intervention thus speeding up the whole process of diagnosis. Overall sensitivity to capture cases of malaria is 100% and specificity ranges from 50-88% for all species of malaria parasites. Image based screening method will speed up the whole process of diagnosis and is more advantageous over laboratory procedures that are prone to errors and where pathological expertise is minimal. Further this method provides a consistent and robust way of generating the parasite clearance curves.

Detecting ship targets in spaceborne infrared image based on modeling radiation anomalies

NASA Astrophysics Data System (ADS)

Wang, Haibo; Zou, Zhengxia; Shi, Zhenwei; Li, Bo

2017-09-01

Using infrared imaging sensors to detect ship target in the ocean environment has many advantages compared to other sensor modalities, such as better thermal sensitivity and all-weather detection capability. We propose a new ship detection method by modeling radiation anomalies for spaceborne infrared image. The proposed method can be decomposed into two stages, where in the first stage, a test infrared image is densely divided into a set of image patches and the radiation anomaly of each patch is estimated by a Gaussian Mixture Model (GMM), and thereby target candidates are obtained from anomaly image patches. In the second stage, target candidates are further checked by a more discriminative criterion to obtain the final detection result. The main innovation of the proposed method is inspired by the biological mechanism that human eyes are sensitive to the unusual and anomalous patches among complex background. The experimental result on short wavelength infrared band (1.560 - 2.300 μm) and long wavelength infrared band (10.30 - 12.50 μm) of Landsat-8 satellite shows the proposed method achieves a desired ship detection accuracy with higher recall than other classical ship detection methods.

Star centroiding error compensation for intensified star sensors.

PubMed

Jiang, Jie; Xiong, Kun; Yu, Wenbo; Yan, Jinyun; Zhang, Guangjun

2016-12-26

A star sensor provides high-precision attitude information by capturing a stellar image; however, the traditional star sensor has poor dynamic performance, which is attributed to its low sensitivity. Regarding the intensified star sensor, the image intensifier is utilized to improve the sensitivity, thereby further improving the dynamic performance of the star sensor. However, the introduction of image intensifier results in star centroiding accuracy decrease, further influencing the attitude measurement precision of the star sensor. A star centroiding error compensation method for intensified star sensors is proposed in this paper to reduce the influences. First, the imaging model of the intensified detector, which includes the deformation parameter of the optical fiber panel, is established based on the orthographic projection through the analysis of errors introduced by the image intensifier. Thereafter, the position errors at the target points based on the model are obtained by using the Levenberg-Marquardt (LM) optimization method. Last, the nearest trigonometric interpolation method is presented to compensate for the arbitrary centroiding error of the image plane. Laboratory calibration result and night sky experiment result show that the compensation method effectively eliminates the error introduced by the image intensifier, thus remarkably improving the precision of the intensified star sensors.

3D elemental sensitive imaging using transmission X-ray microscopy.

PubMed

Liu, Yijin; Meirer, Florian; Wang, Junyue; Requena, Guillermo; Williams, Phillip; Nelson, Johanna; Mehta, Apurva; Andrews, Joy C; Pianetta, Piero

2012-09-01

Determination of the heterogeneous distribution of metals in alloy/battery/catalyst and biological materials is critical to fully characterize and/or evaluate the functionality of the materials. Using synchrotron-based transmission x-ray microscopy (TXM), it is now feasible to perform nanoscale-resolution imaging over a wide X-ray energy range covering the absorption edges of many elements; combining elemental sensitive imaging with determination of sample morphology. We present an efficient and reliable methodology to perform 3D elemental sensitive imaging with excellent sample penetration (tens of microns) using hard X-ray TXM. A sample of an Al-Si piston alloy is used to demonstrate the capability of the proposed method.

Sensitivity and specificity of digital retinal imaging for screening diabetic retinopathy.

PubMed

Lopez-Bastida, J; Cabrera-Lopez, F; Serrano-Aguilar, P

2007-04-01

To assess the effectiveness of a non-mydriatic digital camera (45 degrees -30 degrees photographs) compared with the reference method for screening diabetic retinopathy. Type 1 and 2 diabetic patients (n = 773; 1546 eyes) underwent screening for diabetic retinopathy in a prospective observational study. Hospital-based non-mydriatic digital retinal imaging by a consultant specialist in retinal diseases was compared with slit-lamp biomicroscopy and indirect ophthalmoscopy through dilated pupils, as a gold standard, previously performed in a community health centre by another consultant specialist in retinal diseases. The main outcome measures were sensitivity and specificity of screening methods and prevalence of diabetic retinopathy. The prevalence of any form of diabetic retinopathy was 42.4% (n = 328); the prevalence of sight-threatening including macular oedema and proliferative retinopathy was 9.6% (n = 74). Sensitivity of detection of any diabetic retinopathy by digital imaging was 92% (95% confidence interval 90, 94). Specificity of detection of any diabetic retinopathy was 96% (95, 98). The predictive value of the negative tests was 94% and of a positive test 95%. For sight-threatening retinopathy digital imaging had a sensitivity of 100%. A high sensitivity and specificity are essential for an effective screening programme. These results confirm digital retinal imaging with a non-mydriatic camera as an effective option in community-based screening programmes for diabetic retinopathy.

Robustifying blind image deblurring methods by simple filters

NASA Astrophysics Data System (ADS)

Liu, Yan; Zeng, Xiangrong; Huangpeng, Qizi; Fan, Jun; Zhou, Jinglun; Feng, Jing

2016-07-01

The state-of-the-art blind image deblurring (BID) methods are sensitive to noise, and most of them can deal with only small levels of Gaussian noise. In this paper, we use simple filters to present a robust BID framework which is able to robustify exiting BID methods to high-level Gaussian noise or/and Non-Gaussian noise. Experiments on images in presence of Gaussian noise, impulse noise (salt-and-pepper noise and random-valued noise) and mixed Gaussian-impulse noise, and a real-world blurry and noisy image show that the proposed method can faster estimate sharper kernels and better images, than that obtained by other methods.

A Simple and Effective Image Normalization Method to Monitor Boreal Forest Change in a Siberian Burn Chronosequence across Sensors and across Time

NASA Astrophysics Data System (ADS)

Chen, X.; Vierling, L. A.; Deering, D. W.

2004-12-01

Satellite data offer unique perspectives for monitoring and quantifying land cover change, however, the radiometric consistency among co-located multi-temporal images is difficult to maintain due to variations in sensors and atmosphere. To detect accurate landscape change using multi-temporal images, we developed a new relative radiometric normalization scheme: the temporally invariant cluster (TIC) method. Image data were acquired on 9 June 1990 (Landsat 4), 20 June 2000, and 26 August 2001 (Landsat 7) for analyses over boreal forests near the Siberian city of Krasnoyarsk. Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), and Reduced Simple Ratio (RSR) were investigated in the normalization study. The temporally invariant cluster (TIC) centers were identified through a point density map of the base image and the target image and a normalization regression line was created through all TIC centers. The target image digital data were then converted using the regression function so that the two images could be compared using the resulting common radiometric scale. We found that EVI was very sensitive to vegetation structure and could thus be used to separate conifer forests from deciduous forests and grass/crop lands. NDVI was a very effective vegetation index to reduce the influence of shadow, while EVI was very sensitive to shadowing. After normalization, correlations of NDVI and EVI with field collected total Leaf Area Index (LAI) data in 2000 and 2001 were significantly improved; the r-square values in these regressions increased from 0.49 to 0.69 and from 0.46 to 0.61, respectively. An EVI ¡°cancellation effect¡± where EVI was positively related to understory greenness but negatively related to forest canopy coverage was evident across a post fire chronosequence. These findings indicate that the TIC method provides a simple, effective and repeatable method to create radiometrically comparable data sets for remote detection of landscape change. Compared with some previous relative normalization methods, this new method can avoid subjective selection of a normalization regression line. It does not require high level programming and statistical analyses, yet remains sensitive to landscape changes occurring over seasonal and inter-annual time scales. In addition, the TIC method maintains sensitivity to subtle changes in vegetation phenology and enables normalization even when invariant features are rare.

Dual-axis reflective continuous-wave terahertz confocal scanning polarization imaging and image fusion

NASA Astrophysics Data System (ADS)

Zhou, Yi; Li, Qi

2017-01-01

A dual-axis reflective continuous-wave terahertz (THz) confocal scanning polarization imaging system was adopted. THz polarization imaging experiments on gaps on film and metallic letters "BeLLE" were carried out. Imaging results indicate that the THz polarization imaging is sensitive to the tilted gap or wide flat gap, suggesting the THz polarization imaging is able to detect edges and stains. An image fusion method based on the digital image processing was proposed to ameliorate the imaging quality of metallic letters "BeLLE." Objective and subjective evaluation both prove that this method can improve the imaging quality.

Electromagnetic holographic sensitivity field of two-phase flow in horizontal wells

NASA Astrophysics Data System (ADS)

Zhang, Kuo; Wu, Xi-Ling; Yan, Jing-Fu; Cai, Jia-Tie

2017-03-01

Electromagnetic holographic data are characterized by two modes, suggesting that image reconstruction requires a dual-mode sensitivity field as well. We analyze an electromagnetic holographic field based on tomography theory and Radon inverse transform to derive the expression of the electromagnetic holographic sensitivity field (EMHSF). Then, we apply the EMHSF calculated by using finite-element methods to flow simulations and holographic imaging. The results suggest that the EMHSF based on the partial derivative of radius of the complex electric potential φ is closely linked to the Radon inverse transform and encompasses the sensitivities of the amplitude and phase data. The flow images obtained with inversion using EMHSF better agree with the actual flow patterns. The EMHSF overcomes the limitations of traditional single-mode sensitivity fields.

A comparative study on preprocessing techniques in diabetic retinopathy retinal images: illumination correction and contrast enhancement.

PubMed

Rasta, Seyed Hossein; Partovi, Mahsa Eisazadeh; Seyedarabi, Hadi; Javadzadeh, Alireza

2015-01-01

To investigate the effect of preprocessing techniques including contrast enhancement and illumination correction on retinal image quality, a comparative study was carried out. We studied and implemented a few illumination correction and contrast enhancement techniques on color retinal images to find out the best technique for optimum image enhancement. To compare and choose the best illumination correction technique we analyzed the corrected red and green components of color retinal images statistically and visually. The two contrast enhancement techniques were analyzed using a vessel segmentation algorithm by calculating the sensitivity and specificity. The statistical evaluation of the illumination correction techniques were carried out by calculating the coefficients of variation. The dividing method using the median filter to estimate background illumination showed the lowest Coefficients of variations in the red component. The quotient and homomorphic filtering methods after the dividing method presented good results based on their low Coefficients of variations. The contrast limited adaptive histogram equalization increased the sensitivity of the vessel segmentation algorithm up to 5% in the same amount of accuracy. The contrast limited adaptive histogram equalization technique has a higher sensitivity than the polynomial transformation operator as a contrast enhancement technique for vessel segmentation. Three techniques including the dividing method using the median filter to estimate background, quotient based and homomorphic filtering were found as the effective illumination correction techniques based on a statistical evaluation. Applying the local contrast enhancement technique, such as CLAHE, for fundus images presented good potentials in enhancing the vasculature segmentation.

Computer-aided detection of renal calculi from noncontrast CT images using TV-flow and MSER features

PubMed Central

Liu, Jianfei; Wang, Shijun; Turkbey, Evrim B.; Linguraru, Marius George; Yao, Jianhua; Summers, Ronald M.

2015-01-01

Purpose: Renal calculi are common extracolonic incidental findings on computed tomographic colonography (CTC). This work aims to develop a fully automated computer-aided diagnosis system to accurately detect renal calculi on CTC images. Methods: The authors developed a total variation (TV) flow method to reduce image noise within the kidneys while maintaining the characteristic appearance of renal calculi. Maximally stable extremal region (MSER) features were then calculated to robustly identify calculi candidates. Finally, the authors computed texture and shape features that were imported to support vector machines for calculus classification. The method was validated on a dataset of 192 patients and compared to a baseline approach that detects calculi by thresholding. The authors also compared their method with the detection approaches using anisotropic diffusion and nonsmoothing. Results: At a false positive rate of 8 per patient, the sensitivities of the new method and the baseline thresholding approach were 69% and 35% (p < 1e − 3) on all calculi from 1 to 433 mm3 in the testing dataset. The sensitivities of the detection methods using anisotropic diffusion and nonsmoothing were 36% and 0%, respectively. The sensitivity of the new method increased to 90% if only larger and more clinically relevant calculi were considered. Conclusions: Experimental results demonstrated that TV-flow and MSER features are efficient means to robustly and accurately detect renal calculi on low-dose, high noise CTC images. Thus, the proposed method can potentially improve diagnosis. PMID:25563255

Monte Carlo simulation of the spatial resolution and depth sensitivity of two-dimensional optical imaging of the brain

PubMed Central

Tian, Peifang; Devor, Anna; Sakadžić, Sava; Dale, Anders M.; Boas, David A.

2011-01-01

Absorption or fluorescence-based two-dimensional (2-D) optical imaging is widely employed in functional brain imaging. The image is a weighted sum of the real signal from the tissue at different depths. This weighting function is defined as “depth sensitivity.” Characterizing depth sensitivity and spatial resolution is important to better interpret the functional imaging data. However, due to light scattering and absorption in biological tissues, our knowledge of these is incomplete. We use Monte Carlo simulations to carry out a systematic study of spatial resolution and depth sensitivity for 2-D optical imaging methods with configurations typically encountered in functional brain imaging. We found the following: (i) the spatial resolution is <200 μm for NA ≤0.2 or focal plane depth ≤300 μm. (ii) More than 97% of the signal comes from the top 500 μm of the tissue. (iii) For activated columns with lateral size larger than spatial resolution, changing numerical aperature (NA) and focal plane depth does not affect depth sensitivity. (iv) For either smaller columns or large columns covered by surface vessels, increasing NA and∕or focal plane depth may improve depth sensitivity at deeper layers. Our results provide valuable guidance for the optimization of optical imaging systems and data interpretation. PMID:21280912

Multimodal imaging system for dental caries detection

NASA Astrophysics Data System (ADS)

Liang, Rongguang; Wong, Victor; Marcus, Michael; Burns, Peter; McLaughlin, Paul

2007-02-01

Dental caries is a disease in which minerals of the tooth are dissolved by surrounding bacterial plaques. A caries process present for some time may result in a caries lesion. However, if it is detected early enough, the dentist and dental professionals can implement measures to reverse and control caries. Several optical, nonionized methods have been investigated and used to detect dental caries in early stages. However, there is not a method that can singly detect the caries process with both high sensitivity and high specificity. In this paper, we present a multimodal imaging system that combines visible reflectance, fluorescence, and Optical Coherence Tomography (OCT) imaging. This imaging system is designed to obtain one or more two-dimensional images of the tooth (reflectance and fluorescence images) and a three-dimensional OCT image providing depth and size information of the caries. The combination of two- and three-dimensional images of the tooth has the potential for highly sensitive and specific detection of dental caries.

X-ray lithography using holographic images

DOEpatents

Howells, M.S.; Jacobsen, C.

1997-03-18

Methods for forming X-ray images having 0.25 {micro}m minimum line widths on X-ray sensitive material are presented. A holographic image of a desired circuit pattern is projected onto a wafer or other image-receiving substrate to allow recording of the desired image in photoresist material. In one embodiment, the method uses on-axis transmission and provides a high flux X-ray source having modest monochromaticity and coherence requirements. A layer of light-sensitive photoresist material on a wafer with a selected surface is provided to receive the image(s). The hologram has variable optical thickness and variable associated optical phase angle and amplitude attenuation for transmission of the X-rays. A second embodiment uses off-axis holography. The wafer receives the holographic image by grazing incidence reflection from a hologram printed on a flat metal or other highly reflecting surface or substrate. In this second embodiment, an X-ray beam with a high degree of monochromaticity and spatial coherence is required. 15 figs.

X-ray lithography using holographic images

DOEpatents

Howells, Malcolm S.; Jacobsen, Chris

1997-01-01

Methods for forming X-ray images having 0.25 .mu.m minimum line widths on X-ray sensitive material are presented. A holgraphic image of a desired circuit pattern is projected onto a wafer or other image-receiving substrate to allow recording of the desired image in photoresist material. In one embodiment, the method uses on-axis transmission and provides a high flux X-ray source having modest monochromaticity and coherence requirements. A layer of light-sensitive photoresist material on a wafer with a selected surface is provided to receive the image(s). The hologram has variable optical thickness and variable associated optical phase angle and amplitude attenuation for transmission of the X-rays. A second embodiment uses off-axis holography. The wafer receives the holographic image by grazing incidence reflection from a hologram printed on a flat metal or other highly reflecting surface or substrate. In this second embodiment, an X-ray beam with a high degree of monochromaticity and spatial coherence is required.

Method and apparatus for real time imaging and monitoring of radiotherapy beams

DOEpatents

Majewski, Stanislaw [Yorktown, VA; Proffitt, James [Newport News, VA; Macey, Daniel J [Birmingham, AL; Weisenberger, Andrew G [Yorktown, VA

2011-11-01

A method and apparatus for real time imaging and monitoring of radiation therapy beams is designed to preferentially distinguish and image low energy radiation from high energy secondary radiation emitted from a target as the result of therapeutic beam deposition. A detector having low sensitivity to high energy photons combined with a collimator designed to dynamically image in the region of the therapeutic beam target is used.

Photogrammetry Applied to Wind Tunnel Testing

NASA Technical Reports Server (NTRS)

Liu, Tian-Shu; Cattafesta, L. N., III; Radeztsky, R. H.; Burner, A. W.

2000-01-01

In image-based measurements, quantitative image data must be mapped to three-dimensional object space. Analytical photogrammetric methods, which may be used to accomplish this task, are discussed from the viewpoint of experimental fluid dynamicists. The Direct Linear Transformation (DLT) for camera calibration, used in pressure sensitive paint, is summarized. An optimization method for camera calibration is developed that can be used to determine the camera calibration parameters, including those describing lens distortion, from a single image. Combined with the DLT method, this method allows a rapid and comprehensive in-situ camera calibration and therefore is particularly useful for quantitative flow visualization and other measurements such as model attitude and deformation in production wind tunnels. The paper also includes a brief description of typical photogrammetric applications to temperature- and pressure-sensitive paint measurements and model deformation measurements in wind tunnels.

Characterization of Window Functions for Regularization of Electrical Capacitance Tomography Image Reconstruction

NASA Astrophysics Data System (ADS)

Jiang, Peng; Peng, Lihui; Xiao, Deyun

2007-06-01

This paper presents a regularization method by using different window functions as regularization for electrical capacitance tomography (ECT) image reconstruction. Image reconstruction for ECT is a typical ill-posed inverse problem. Because of the small singular values of the sensitivity matrix, the solution is sensitive to the measurement noise. The proposed method uses the spectral filtering properties of different window functions to make the solution stable by suppressing the noise in measurements. The window functions, such as the Hanning window, the cosine window and so on, are modified for ECT image reconstruction. Simulations with respect to five typical permittivity distributions are carried out. The reconstructions are better and some of the contours are clearer than the results from the Tikhonov regularization. Numerical results show that the feasibility of the image reconstruction algorithm using different window functions as regularization.

Chemical imaging analysis of the brain with X-ray methods

NASA Astrophysics Data System (ADS)

Collingwood, Joanna F.; Adams, Freddy

2017-04-01

Cells employ various metal and metalloid ions to augment the structure and the function of proteins and to assist with vital biological processes. In the brain they mediate biochemical processes, and disrupted metabolism of metals may be a contributing factor in neurodegenerative disorders. In this tutorial review we will discuss the particular role of X-ray methods for elemental imaging analysis of accumulated metal species and metal-containing compounds in biological materials, in the context of post-mortem brain tissue. X-rays have the advantage that they have a short wavelength and can penetrate through a thick biological sample. Many of the X-ray microscopy techniques that provide the greatest sensitivity and specificity for trace metal concentrations in biological materials are emerging at synchrotron X-ray facilities. Here, the extremely high flux available across a wide range of soft and hard X-rays, combined with state-of-the-art focusing techniques and ultra-sensitive detectors, makes it viable to undertake direct imaging of a number of elements in brain tissue. The different methods for synchrotron imaging of metals in brain tissues at regional, cellular, and sub-cellular spatial resolution are discussed. Methods covered include X-ray fluorescence for elemental imaging, X-ray absorption spectrometry for speciation imaging, X-ray diffraction for structural imaging, phase contrast for enhanced contrast imaging and scanning transmission X-ray microscopy for spectromicroscopy. Two- and three-dimensional (confocal and tomographic) imaging methods are considered as well as the correlation of X-ray microscopy with other imaging tools.

Optical Brain Imaging: A Powerful Tool for Neuroscience.

PubMed

Zhu, Xinpei; Xia, Yanfang; Wang, Xuecen; Si, Ke; Gong, Wei

2017-02-01

As the control center of organisms, the brain remains little understood due to its complexity. Taking advantage of imaging methods, scientists have found an accessible approach to unraveling the mystery of neuroscience. Among these methods, optical imaging techniques are widely used due to their high molecular specificity and single-molecule sensitivity. Here, we overview several optical imaging techniques in neuroscience of recent years, including brain clearing, the micro-optical sectioning tomography system, and deep tissue imaging.

Probe-Specific Procedure to Estimate Sensitivity and Detection Limits for 19F Magnetic Resonance Imaging.

PubMed

Taylor, Alexander J; Granwehr, Josef; Lesbats, Clémentine; Krupa, James L; Six, Joseph S; Pavlovskaya, Galina E; Thomas, Neil R; Auer, Dorothee P; Meersmann, Thomas; Faas, Henryk M

2016-01-01

Due to low fluorine background signal in vivo, 19F is a good marker to study the fate of exogenous molecules by magnetic resonance imaging (MRI) using equilibrium nuclear spin polarization schemes. Since 19F MRI applications require high sensitivity, it can be important to assess experimental feasibility during the design stage already by estimating the minimum detectable fluorine concentration. Here we propose a simple method for the calibration of MRI hardware, providing sensitivity estimates for a given scanner and coil configuration. An experimental "calibration factor" to account for variations in coil configuration and hardware set-up is specified. Once it has been determined in a calibration experiment, the sensitivity of an experiment or, alternatively, the minimum number of required spins or the minimum marker concentration can be estimated without the need for a pilot experiment. The definition of this calibration factor is derived based on standard equations for the sensitivity in magnetic resonance, yet the method is not restricted by the limited validity of these equations, since additional instrument-dependent factors are implicitly included during calibration. The method is demonstrated using MR spectroscopy and imaging experiments with different 19F samples, both paramagnetically and susceptibility broadened, to approximate a range of realistic environments.

Improved sensitivity of computed tomography towards iodine and gold nanoparticle contrast agents via iterative reconstruction methods

PubMed Central

Bernstein, Ally Leigh; Dhanantwari, Amar; Jurcova, Martina; Cheheltani, Rabee; Naha, Pratap Chandra; Ivanc, Thomas; Shefer, Efrat; Cormode, David Peter

2016-01-01

Computed tomography is a widely used medical imaging technique that has high spatial and temporal resolution. Its weakness is its low sensitivity towards contrast media. Iterative reconstruction techniques (ITER) have recently become available, which provide reduced image noise compared with traditional filtered back-projection methods (FBP), which may allow the sensitivity of CT to be improved, however this effect has not been studied in detail. We scanned phantoms containing either an iodine contrast agent or gold nanoparticles. We used a range of tube voltages and currents. We performed reconstruction with FBP, ITER and a novel, iterative, modal-based reconstruction (IMR) algorithm. We found that noise decreased in an algorithm dependent manner (FBP > ITER > IMR) for every scan and that no differences were observed in attenuation rates of the agents. The contrast to noise ratio (CNR) of iodine was highest at 80 kV, whilst the CNR for gold was highest at 140 kV. The CNR of IMR images was almost tenfold higher than that of FBP images. Similar trends were found in dual energy images formed using these algorithms. In conclusion, IMR-based reconstruction techniques will allow contrast agents to be detected with greater sensitivity, and may allow lower contrast agent doses to be used. PMID:27185492

Portal dosimetry for VMAT using integrated images obtained during treatment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bedford, James L., E-mail: James.Bedford@icr.ac.uk; Hanson, Ian M.; Hansen, Vibeke Nordmark

2014-02-15

Purpose: Portal dosimetry provides an accurate and convenient means of verifying dose delivered to the patient. A simple method for carrying out portal dosimetry for volumetric modulated arc therapy (VMAT) is described, together with phantom measurements demonstrating the validity of the approach. Methods: Portal images were predicted by projecting dose in the isocentric plane through to the portal image plane, with exponential attenuation and convolution with a double-Gaussian scatter function. Appropriate parameters for the projection were selected by fitting the calculation model to portal images measured on an iViewGT portal imager (Elekta AB, Stockholm, Sweden) for a variety of phantommore » thicknesses and field sizes. This model was then used to predict the portal image resulting from each control point of a VMAT arc. Finally, all these control point images were summed to predict the overall integrated portal image for the whole arc. The calculated and measured integrated portal images were compared for three lung and three esophagus plans delivered to a thorax phantom, and three prostate plans delivered to a homogeneous phantom, using a gamma index for 3% and 3 mm. A 0.6 cm{sup 3} ionization chamber was used to verify the planned isocentric dose. The sensitivity of this method to errors in monitor units, field shaping, gantry angle, and phantom position was also evaluated by means of computer simulations. Results: The calculation model for portal dose prediction was able to accurately compute the portal images due to simple square fields delivered to solid water phantoms. The integrated images of VMAT treatments delivered to phantoms were also correctly predicted by the method. The proportion of the images with a gamma index of less than unity was 93.7% ± 3.0% (1SD) and the difference between isocenter dose calculated by the planning system and measured by the ionization chamber was 0.8% ± 1.0%. The method was highly sensitive to errors in monitor units and field shape, but less sensitive to errors in gantry angle or phantom position. Conclusions: This method of predicting integrated portal images provides a convenient means of verifying dose delivered using VMAT, with minimal image acquisition and data processing requirements.« less

POCS-enhanced correction of motion artifacts in parallel MRI.

PubMed

Samsonov, Alexey A; Velikina, Julia; Jung, Youngkyoo; Kholmovski, Eugene G; Johnson, Chris R; Block, Walter F

2010-04-01

A new method for correction of MRI motion artifacts induced by corrupted k-space data, acquired by multiple receiver coils such as phased arrays, is presented. In our approach, a projections onto convex sets (POCS)-based method for reconstruction of sensitivity encoded MRI data (POCSENSE) is employed to identify corrupted k-space samples. After the erroneous data are discarded from the dataset, the artifact-free images are restored from the remaining data using coil sensitivity profiles. The error detection and data restoration are based on informational redundancy of phased-array data and may be applied to full and reduced datasets. An important advantage of the new POCS-based method is that, in addition to multicoil data redundancy, it can use a priori known properties about the imaged object for improved MR image artifact correction. The use of such information was shown to improve significantly k-space error detection and image artifact correction. The method was validated on data corrupted by simulated and real motion such as head motion and pulsatile flow.

Assessing the Potential of Metal-Assisted Imaging Mass Spectrometry in Cancer Research.

PubMed

Dufresne, M; Patterson, N H; Lauzon, N; Chaurand, P

2017-01-01

In the last decade, imaging mass spectrometry (IMS) has been the primary tool for biomolecular imaging. While it is possible to map a wide range of biomolecules using matrix-assisted laser desorption/ionization IMS ranging from high-molecular-weight proteins to small metabolites, more often than not only the most abundant easily ionisable species are detected. To better understand complex diseases such as cancer more specific and sensitive methods need to be developed to enable the detection of lower abundance molecules but also molecules that have yet to be imaged by IMS. In recent years, a big shift has occurred in the imaging community from developing wide reaching methods to developing targeted ones which increases sensitivity through the use of more specific sample preparations. This has been primarily marked by the advent of solvent-free matrix deposition methods for polar lipids, chemical derivatization for hormones and metabolites, and the use of alternative ionization agents for neutral lipids. In this chapter, we discuss two of the latest sample preparations which exploit the use of alternative ionization agents to enable the detection of certain classes of neutral lipids along with free fatty acids by high-sensitivity IMS as demonstrated within our lab. © 2017 Elsevier Inc. All rights reserved.

Computer-aided detection of renal calculi from noncontrast CT images using TV-flow and MSER features.

PubMed

Liu, Jianfei; Wang, Shijun; Turkbey, Evrim B; Linguraru, Marius George; Yao, Jianhua; Summers, Ronald M

2015-01-01

Renal calculi are common extracolonic incidental findings on computed tomographic colonography (CTC). This work aims to develop a fully automated computer-aided diagnosis system to accurately detect renal calculi on CTC images. The authors developed a total variation (TV) flow method to reduce image noise within the kidneys while maintaining the characteristic appearance of renal calculi. Maximally stable extremal region (MSER) features were then calculated to robustly identify calculi candidates. Finally, the authors computed texture and shape features that were imported to support vector machines for calculus classification. The method was validated on a dataset of 192 patients and compared to a baseline approach that detects calculi by thresholding. The authors also compared their method with the detection approaches using anisotropic diffusion and nonsmoothing. At a false positive rate of 8 per patient, the sensitivities of the new method and the baseline thresholding approach were 69% and 35% (p < 1e - 3) on all calculi from 1 to 433 mm(3) in the testing dataset. The sensitivities of the detection methods using anisotropic diffusion and nonsmoothing were 36% and 0%, respectively. The sensitivity of the new method increased to 90% if only larger and more clinically relevant calculi were considered. Experimental results demonstrated that TV-flow and MSER features are efficient means to robustly and accurately detect renal calculi on low-dose, high noise CTC images. Thus, the proposed method can potentially improve diagnosis.

Direct magnetic field estimation based on echo planar raw data.

PubMed

Testud, Frederik; Splitthoff, Daniel Nicolas; Speck, Oliver; Hennig, Jürgen; Zaitsev, Maxim

2010-07-01

Gradient recalled echo echo planar imaging is widely used in functional magnetic resonance imaging. The fast data acquisition is, however, very sensitive to field inhomogeneities which manifest themselves as artifacts in the images. Typically used correction methods have the common deficit that the data for the correction are acquired only once at the beginning of the experiment, assuming the field inhomogeneity distribution B(0) does not change over the course of the experiment. In this paper, methods to extract the magnetic field distribution from the acquired k-space data or from the reconstructed phase image of a gradient echo planar sequence are compared and extended. A common derivation for the presented approaches provides a solid theoretical basis, enables a fair comparison and demonstrates the equivalence of the k-space and the image phase based approaches. The image phase analysis is extended here to calculate the local gradient in the readout direction and improvements are introduced to the echo shift analysis, referred to here as "k-space filtering analysis." The described methods are compared to experimentally acquired B(0) maps in phantoms and in vivo. The k-space filtering analysis presented in this work demonstrated to be the most sensitive method to detect field inhomogeneities.

POCS-based reconstruction of multiplexed sensitivity encoded MRI (POCSMUSE): a general algorithm for reducing motion-related artifacts

PubMed Central

Chu, Mei-Lan; Chang, Hing-Chiu; Chung, Hsiao-Wen; Truong, Trong-Kha; Bashir, Mustafa R.; Chen, Nan-kuei

2014-01-01

Purpose A projection onto convex sets reconstruction of multiplexed sensitivity encoded MRI (POCSMUSE) is developed to reduce motion-related artifacts, including respiration artifacts in abdominal imaging and aliasing artifacts in interleaved diffusion weighted imaging (DWI). Theory Images with reduced artifacts are reconstructed with an iterative POCS procedure that uses the coil sensitivity profile as a constraint. This method can be applied to data obtained with different pulse sequences and k-space trajectories. In addition, various constraints can be incorporated to stabilize the reconstruction of ill-conditioned matrices. Methods The POCSMUSE technique was applied to abdominal fast spin-echo imaging data, and its effectiveness in respiratory-triggered scans was evaluated. The POCSMUSE method was also applied to reduce aliasing artifacts due to shot-to-shot phase variations in interleaved DWI data corresponding to different k-space trajectories and matrix condition numbers. Results Experimental results show that the POCSMUSE technique can effectively reduce motion-related artifacts in data obtained with different pulse sequences, k-space trajectories and contrasts. Conclusion POCSMUSE is a general post-processing algorithm for reduction of motion-related artifacts. It is compatible with different pulse sequences, and can also be used to further reduce residual artifacts in data produced by existing motion artifact reduction methods. PMID:25394325

Highly sensitive fluorescence detection of metastatic lymph nodes of gastric cancer with photo-oxidation of protoporphyrin IX.

PubMed

Koizumi, N; Harada, Y; Beika, M; Minamikawa, T; Yamaoka, Y; Dai, P; Murayama, Y; Yanagisawa, A; Otsuji, E; Tanaka, H; Takamatsu, T

2016-08-01

The establishment of a precise and rapid method to detect metastatic lymph nodes (LNs) is essential to perform less invasive surgery with reduced gastrectomy along with reduced lymph node dissection. We herein describe a novel imaging strategy to detect 5-aminolevulinic acid (5-ALA)-induced protoporphyrin IX (PpIX) fluorescence in excised LNs specifically with reduced effects of tissue autofluorescence based on photo-oxidation of PpIX. We applied the method in a clinical setting, and evaluated its feasibility. To reduce the unfavorable effect of autofluorescence, we focused on photo-oxidation of PpIX: Following light irradiation, PpIX changes into another substance, photo-protoporphyrin, via an oxidative process, which has a different spectral peak, at 675 nm, whereas PpIX has its spectral peak at 635 nm. Based on the unique spectral alteration, fluorescence spectral imaging before and after light irradiation and subsequent originally-developed image processing was performed. Following in vitro study, we applied this method to a total of 662 excised LNs obtained from 30 gastric cancer patients administered 5-ALA preoperatively. Specific visualization of PpIX was achieved in in vitro study. The method allowed highly sensitive detection of metastatic LNs, with sensitivity of 91.9% and specificity of 90.8% in the in vivo clinical trial. Receiver operating characteristic analysis indicated high diagnostic accuracy, with the area under the curve of 0.926. We established a highly sensitive and specific 5-ALA-induced fluorescence imaging method applicable in clinical settings. The novel method has a potential to become a useful tool for intraoperative rapid diagnosis of LN metastasis. Copyright © 2016 Elsevier Ltd. All rights reserved.

Back-illuminated imager and method for making electrical and optical connections to same

NASA Technical Reports Server (NTRS)

Pain, Bedabrata (Inventor)

2010-01-01

Methods for bringing or exposing metal pads or traces to the backside of a backside-illuminated imager allow the pads or traces to reside on the illumination side for electrical connection. These methods provide a solution to a key packaging problem for backside thinned imagers. The methods also provide alignment marks for integrating color filters and microlenses to the imager pixels residing on the frontside of the wafer, enabling high performance multispectral and high sensitivity imagers, including those with extremely small pixel pitch. In addition, the methods incorporate a passivation layer for protection of devices against external contamination, and allow interface trap density reduction via thermal annealing. Backside-illuminated imagers with illumination side electrical connections are also disclosed.

Nonlinear PET parametric image reconstruction with MRI information using kernel method

NASA Astrophysics Data System (ADS)

Gong, Kuang; Wang, Guobao; Chen, Kevin T.; Catana, Ciprian; Qi, Jinyi

2017-03-01

Positron Emission Tomography (PET) is a functional imaging modality widely used in oncology, cardiology, and neurology. It is highly sensitive, but suffers from relatively poor spatial resolution, as compared with anatomical imaging modalities, such as magnetic resonance imaging (MRI). With the recent development of combined PET/MR systems, we can improve the PET image quality by incorporating MR information. Previously we have used kernel learning to embed MR information in static PET reconstruction and direct Patlak reconstruction. Here we extend this method to direct reconstruction of nonlinear parameters in a compartment model by using the alternating direction of multiplier method (ADMM) algorithm. Simulation studies show that the proposed method can produce superior parametric images compared with existing methods.

Prediction of venous wound healing with laser speckle imaging.

PubMed

van Vuuren, Timme Maj; Van Zandvoort, Carina; Doganci, Suat; Zwiers, Ineke; tenCate-Hoek, Arina J; Kurstjens, Ralph Lm; Wittens, Cees Ha

2017-12-01

Introduction Laser speckle imaging is used for noninvasive assessment of blood flow of cutaneous wounds. The aim of this study was to assess if laser speckle imaging can be used as a predictor of venous ulcer healing. Methods After generating the flux speckle images, three regions of interest (ROI) were identified to measure the flow. Sensitivity, specificity, negative predictive value, and positive predictive value for ulcer healing were calculated. Results In total, 17 limbs were included. A sensitivity of 92.3%, specificity of 75.0%, PPV of 80.0%, and NPV 75.0% were found in predicting wound healing based on laser speckle images. Mean flux values were lowest in the center (ROI I) and showed an increase at the wound edge (ROI II, p = 0.03). Conclusion Laser speckle imaging shows acceptable sensitivity and specificity rates in predicting venous ulcer healing. The wound edge proved to be the best probability for the prediction of wound healing.

Tumor margin assessment of surgical tissue specimen of cancer patients using label-free hyperspectral imaging

NASA Astrophysics Data System (ADS)

Fei, Baowei; Lu, Guolan; Wang, Xu; Zhang, Hongzheng; Little, James V.; Magliocca, Kelly R.; Chen, Amy Y.

2017-02-01

We are developing label-free hyperspectral imaging (HSI) for tumor margin assessment. HSI data, hypercube (x,y,λ), consists of a series of high-resolution images of the same field of view that are acquired at different wavelengths. Every pixel on the HSI image has an optical spectrum. We developed preprocessing and classification methods for HSI data. We used spectral features from HSI data for the classification of cancer and benign tissue. We collected surgical tissue specimens from 16 human patients who underwent head and neck (H&N) cancer surgery. We acquired both HSI, autofluorescence images, and fluorescence images with 2-NBDG and proflavine from the specimens. Digitized histologic slides were examined by an H&N pathologist. The hyperspectral imaging and classification method was able to distinguish between cancer and normal tissue from oral cavity with an average accuracy of 90+/-8%, sensitivity of 89+/-9%, and specificity of 91+/-6%. For tissue specimens from the thyroid, the method achieved an average accuracy of 94+/-6%, sensitivity of 94+/-6%, and specificity of 95+/-6%. Hyperspectral imaging outperformed autofluorescence imaging or fluorescence imaging with vital dye (2-NBDG or proflavine). This study suggests that label-free hyperspectral imaging has great potential for tumor margin assessment in surgical tissue specimens of H&N cancer patients. Further development of the hyperspectral imaging technology is warranted for its application in image-guided surgery.

Rapid, low dose X-ray diffractive imaging of the malaria parasite Plasmodium falciparum.

PubMed

Jones, Michael W M; Dearnley, Megan K; van Riessen, Grant A; Abbey, Brian; Putkunz, Corey T; Junker, Mark D; Vine, David J; McNulty, Ian; Nugent, Keith A; Peele, Andrew G; Tilley, Leann

2014-08-01

Phase-diverse X-ray coherent diffractive imaging (CDI) provides a route to high sensitivity and spatial resolution with moderate radiation dose. It also provides a robust solution to the well-known phase-problem, making on-line image reconstruction feasible. Here we apply phase-diverse CDI to a cellular sample, obtaining images of an erythrocyte infected by the sexual stage of the malaria parasite, Plasmodium falciparum, with a radiation dose significantly lower than the lowest dose previously reported for cellular imaging using CDI. The high sensitivity and resolution allow key biological features to be identified within intact cells, providing complementary information to optical and electron microscopy. This high throughput method could be used for fast tomographic imaging, or to generate multiple replicates in two-dimensions of hydrated biological systems without freezing or fixing. This work demonstrates that phase-diverse CDI is a valuable complementary imaging method for the biological sciences and ready for immediate application. © 2013 Elsevier B.V. All rights reserved.

Pattern-projected schlieren imaging method using a diffractive optics element

NASA Astrophysics Data System (ADS)

Min, Gihyeon; Lee, Byung-Tak; Kim, Nac Woo; Lee, Munseob

2018-04-01

We propose a novel schlieren imaging method by projecting a random dot pattern, which is generated in a light source module that includes a diffractive optical element. All apparatuses are located in the source side, which leads to one-body sensor applications. This pattern is distorted by the deflections of schlieren objects such that the displacement vectors of random dots in the pixels can be obtained using the particle image velocity algorithm. The air turbulences induced by a burning candle, boiling pot, heater, and gas torch were successfully imaged, and it was shown that imaging up to a size of 0.7 m  ×  0.57 m is possible. An algorithm to correct the non-uniform sensitivity according to the position of a schlieren object was analytically derived. This algorithm was applied to schlieren images of lenses. Comparing the corrected versions to the original schlieren images, we showed a corrected uniform sensitivity of 14.15 times on average.

Telescope for x ray and gamma ray studies in astrophysics

NASA Technical Reports Server (NTRS)

Weaver, W. D.; Desai, Upendra D.

1993-01-01

Imaging of x-rays has been achieved by various methods in astrophysics, nuclear physics, medicine, and material science. A new method for imaging x-ray and gamma-ray sources avoids the limitations of previously used imaging devices. Images are formed in optical wavelengths by using mirrors or lenses to reflect and refract the incoming photons. High energy x-ray and gamma-ray photons cannot be reflected except at grazing angles and pass through lenses without being refracted. Therefore, different methods must be used to image x-ray and gamma-ray sources. Techniques using total absorption, or shadow casting, can provide images in x-rays and gamma-rays. This new method uses a coder made of a pair of Fresnel zone plates and a detector consisting of a matrix of CsI scintillators and photodiodes. The Fresnel zone plates produce Moire patterns when illuminated by an off-axis source. These Moire patterns are deconvolved using a stepped sine wave fitting or an inverse Fourier transform. This type of coder provides the capability of an instantaneous image with sub-arcminute resolution while using a detector with only a coarse position-sensitivity. A matrix of the CsI/photodiode detector elements provides the necessary coarse position-sensitivity. The CsI/photodiode detector also allows good energy resolution. This imaging system provides advantages over previously used imaging devices in both performance and efficiency.

Improved In vivo Assessment of Pulmonary Fibrosis in Mice using X-Ray Dark-Field Radiography

NASA Astrophysics Data System (ADS)

Yaroshenko, Andre; Hellbach, Katharina; Yildirim, Ali Önder; Conlon, Thomas M.; Fernandez, Isis Enlil; Bech, Martin; Velroyen, Astrid; Meinel, Felix G.; Auweter, Sigrid; Reiser, Maximilian; Eickelberg, Oliver; Pfeiffer, Franz

2015-12-01

Idiopathic pulmonary fibrosis (IPF) is a chronic and progressive lung disease with a median life expectancy of 4-5 years after initial diagnosis. Early diagnosis and accurate monitoring of IPF are limited by a lack of sensitive imaging techniques that are able to visualize early fibrotic changes at the epithelial-mesenchymal interface. Here, we report a new x-ray imaging approach that directly visualizes the air-tissue interfaces in mice in vivo. This imaging method is based on the detection of small-angle x-ray scattering that occurs at the air-tissue interfaces in the lung. Small-angle scattering is detected with a Talbot-Lau interferometer, which provides the so-called x-ray dark-field signal. Using this imaging modality, we demonstrate-for the first time-the quantification of early pathogenic changes and their correlation with histological changes, as assessed by stereological morphometry. The presented radiography method is significantly more sensitive in detecting morphological changes compared with conventional x-ray imaging, and exhibits a significantly lower radiation dose than conventional x-ray CT. As a result of the improved imaging sensitivity, this new imaging modality could be used in future to reduce the number of animals required for pulmonary research studies.

A multi-scale tensor voting approach for small retinal vessel segmentation in high resolution fundus images.

PubMed

Christodoulidis, Argyrios; Hurtut, Thomas; Tahar, Houssem Ben; Cheriet, Farida

2016-09-01

Segmenting the retinal vessels from fundus images is a prerequisite for many CAD systems for the automatic detection of diabetic retinopathy lesions. So far, research efforts have concentrated mainly on the accurate localization of the large to medium diameter vessels. However, failure to detect the smallest vessels at the segmentation step can lead to false positive lesion detection counts in a subsequent lesion analysis stage. In this study, a new hybrid method for the segmentation of the smallest vessels is proposed. Line detection and perceptual organization techniques are combined in a multi-scale scheme. Small vessels are reconstructed from the perceptual-based approach via tracking and pixel painting. The segmentation was validated in a high resolution fundus image database including healthy and diabetic subjects using pixel-based as well as perceptual-based measures. The proposed method achieves 85.06% sensitivity rate, while the original multi-scale line detection method achieves 81.06% sensitivity rate for the corresponding images (p<0.05). The improvement in the sensitivity rate for the database is 6.47% when only the smallest vessels are considered (p<0.05). For the perceptual-based measure, the proposed method improves the detection of the vasculature by 7.8% against the original multi-scale line detection method (p<0.05). Copyright © 2016 Elsevier Ltd. All rights reserved.

Imaging alpha particle detector

DOEpatents

Anderson, David F.

1985-01-01

A method and apparatus for detecting and imaging alpha particles sources is described. A conducting coated high voltage electrode (1) and a tungsten wire grid (2) constitute a diode configuration discharge generator for electrons dislodged from atoms or molecules located in between these electrodes when struck by alpha particles from a source (3) to be quantitatively or qualitatively analyzed. A thin polyester film window (4) allows the alpha particles to pass into the gas enclosure and the combination of the glass electrode, grid and window is light transparent such that the details of the source which is imaged with high resolution and sensitivity by the sparks produced can be observed visually as well. The source can be viewed directly, electronically counted or integrated over time using photographic methods. A significant increase in sensitivity over other alpha particle detectors is observed, and the device has very low sensitivity to gamma or beta emissions which might otherwise appear as noise on the alpha particle signal.

Imaging alpha particle detector

DOEpatents

Anderson, D.F.

1980-10-29

A method and apparatus for detecting and imaging alpha particles sources is described. A dielectric coated high voltage electrode and a tungsten wire grid constitute a diode configuration discharge generator for electrons dislodged from atoms or molecules located in between these electrodes when struck by alpha particles from a source to be quantitatively or qualitatively analyzed. A thin polyester film window allows the alpha particles to pass into the gas enclosure and the combination of the glass electrode, grid and window is light transparent such that the details of the source which is imaged with high resolution and sensitivity by the sparks produced can be observed visually as well. The source can be viewed directly, electronically counted or integrated over time using photographic methods. A significant increase in sensitivity over other alpha particle detectors is observed, and the device has very low sensitivity to gamma or beta emissions which might otherwise appear as noise on the alpha particle signal.

Solar monochromatic images in magneto-sensitive spectral lines and maps of vector magnetic fields

NASA Technical Reports Server (NTRS)

Shihui, Y.; Jiehai, J.; Minhan, J.

1985-01-01

A new method which allows by use of the monochromatic images in some magneto-sensitive spectra line to derive both the magnetic field strength as well as the angle between magnetic field lines and line of sight for various places in solar active regions is described. In this way two dimensional maps of vector magnetic fields may be constructed. This method was applied to some observational material and reasonable results were obtained. In addition, a project for constructing the three dimensional maps of vector magnetic fields was worked out.

Comparison of lifetime-based methods for 2D phosphor thermometry in high-temperature environment

NASA Astrophysics Data System (ADS)

Peng, Di; Liu, Yingzheng; Zhao, Xiaofeng; Kim, Kyung Chun

2016-09-01

This paper discusses the currently available techniques for 2D phosphor thermometry, and compares the performance of two lifetime-based methods: high-speed imaging and the dual-gate. High-speed imaging resolves luminescent decay with a fast frame rate, and has become a popular method for phosphor thermometry in recent years. But it has disadvantages such as high equipment cost and long data processing time, and it would fail at sufficiently high temperature due to a low signal-to-noise ratio and short lifetime. The dual-gate method only requires two images on the decay curve and therefore greatly reduces cost in hardware and processing time. A dual-gate method for phosphor thermometry has been developed and compared with the high-speed imaging method through both calibration and a jet impingement experiment. Measurement uncertainty has been evaluated for a temperature range of 473-833 K. The effects of several key factors on uncertainty have been discussed, including the luminescent signal level, the decay lifetime and temperature sensitivity. The results show that both methods are valid for 2D temperature sensing within the given range. The high-speed imaging method shows less uncertainty at low temperatures where the signal level and the lifetime are both sufficient, but its performance is degraded at higher temperatures due to a rapidly reduced signal and lifetime. For T  >  750 K, the dual-gate method outperforms the high-speed imaging method thanks to its superiority in signal-to-noise ratio and temperature sensitivity. The dual-gate method has great potential for applications in high-temperature environments where the high-speed imaging method is not applicable.

Optimum parameters of image preprocessing method for Shack-Hartmann wavefront sensor in different SNR condition

NASA Astrophysics Data System (ADS)

Wei, Ping; Li, Xinyang; Luo, Xi; Li, Jianfeng

2018-02-01

The centroid method is commonly adopted to locate the spot in the sub-apertures in the Shack-Hartmann wavefront sensor (SH-WFS), in which preprocessing image is required before calculating the spot location due to that the centroid method is extremely sensitive to noises. In this paper, the SH-WFS image was simulated according to the characteristics of the noises, background and intensity distribution. The Optimal parameters of SH-WFS image preprocessing method were put forward, in different signal-to-noise ratio (SNR) conditions, where the wavefront reconstruction error was considered as the evaluation index. Two methods of image preprocessing, thresholding method and windowing combing with thresholding method, were compared by studying the applicable range of SNR and analyzing the stability of the two methods, respectively.

A Comparative Study on Preprocessing Techniques in Diabetic Retinopathy Retinal Images: Illumination Correction and Contrast Enhancement

PubMed Central

Rasta, Seyed Hossein; Partovi, Mahsa Eisazadeh; Seyedarabi, Hadi; Javadzadeh, Alireza

2015-01-01

To investigate the effect of preprocessing techniques including contrast enhancement and illumination correction on retinal image quality, a comparative study was carried out. We studied and implemented a few illumination correction and contrast enhancement techniques on color retinal images to find out the best technique for optimum image enhancement. To compare and choose the best illumination correction technique we analyzed the corrected red and green components of color retinal images statistically and visually. The two contrast enhancement techniques were analyzed using a vessel segmentation algorithm by calculating the sensitivity and specificity. The statistical evaluation of the illumination correction techniques were carried out by calculating the coefficients of variation. The dividing method using the median filter to estimate background illumination showed the lowest Coefficients of variations in the red component. The quotient and homomorphic filtering methods after the dividing method presented good results based on their low Coefficients of variations. The contrast limited adaptive histogram equalization increased the sensitivity of the vessel segmentation algorithm up to 5% in the same amount of accuracy. The contrast limited adaptive histogram equalization technique has a higher sensitivity than the polynomial transformation operator as a contrast enhancement technique for vessel segmentation. Three techniques including the dividing method using the median filter to estimate background, quotient based and homomorphic filtering were found as the effective illumination correction techniques based on a statistical evaluation. Applying the local contrast enhancement technique, such as CLAHE, for fundus images presented good potentials in enhancing the vasculature segmentation. PMID:25709940

Redundancy Analysis of Capacitance Data of a Coplanar Electrode Array for Fast and Stable Imaging Processing

PubMed Central

Wen, Yintang; Zhang, Zhenda; Zhang, Yuyan; Sun, Dongtao

2017-01-01

A coplanar electrode array sensor is established for the imaging of composite-material adhesive-layer defect detection. The sensor is based on the capacitive edge effect, which leads to capacitance data being considerably weak and susceptible to environmental noise. The inverse problem of coplanar array electrical capacitance tomography (C-ECT) is ill-conditioning, in which a small error of capacitance data can seriously affect the quality of reconstructed images. In order to achieve a stable image reconstruction process, a redundancy analysis method for capacitance data is proposed. The proposed method is based on contribution rate and anti-interference capability. According to the redundancy analysis, the capacitance data are divided into valid and invalid data. When the image is reconstructed by valid data, the sensitivity matrix needs to be changed accordingly. In order to evaluate the effectiveness of the sensitivity map, singular value decomposition (SVD) is used. Finally, the two-dimensional (2D) and three-dimensional (3D) images are reconstructed by the Tikhonov regularization method. Through comparison of the reconstructed images of raw capacitance data, the stability of the image reconstruction process can be improved, and the quality of reconstructed images is not degraded. As a result, much invalid data are not collected, and the data acquisition time can also be reduced. PMID:29295537

Clustering Multiple Sclerosis Subgroups with Multifractal Methods and Self-Organizing Map Algorithm

NASA Astrophysics Data System (ADS)

Karaca, Yeliz; Cattani, Carlo

Magnetic resonance imaging (MRI) is the most sensitive method to detect chronic nervous system diseases such as multiple sclerosis (MS). In this paper, Brownian motion Hölder regularity functions (polynomial, periodic (sine), exponential) for 2D image, such as multifractal methods were applied to MR brain images, aiming to easily identify distressed regions, in MS patients. With these regions, we have proposed an MS classification based on the multifractal method by using the Self-Organizing Map (SOM) algorithm. Thus, we obtained a cluster analysis by identifying pixels from distressed regions in MR images through multifractal methods and by diagnosing subgroups of MS patients through artificial neural networks.

Advances in serological, imaging techniques and molecular diagnosis of Toxoplasma gondii infection.

PubMed

Rostami, Ali; Karanis, Panagiotis; Fallahi, Shirzad

2018-06-01

Toxoplasmosis is worldwide distributed zoonotic infection disease with medical importance in immunocompromised patients, pregnant women and congenitally infected newborns. Having basic information on the traditional and new developed methods is essential for general physicians and infectious disease specialists for choosing a suitable diagnostic approach for rapid and accurate diagnosis of the disease and, consequently, timely and effective treatment. We conducted English literature searches in PubMed from 1989 to 2016 using relevant keywords and summarized the recent advances in diagnosis of toxoplasmosis. Enzyme-linked immunosorbent assay (ELISA) was most used method in past century. Recently advanced ELISA-based methods including chemiluminescence assays (CLIA), enzyme-linked fluorescence assay (ELFA), immunochromatographic test (ICT), serum IgG avidity test and immunosorbent agglutination assays (ISAGA) have shown high sensitivity and specificity. Recent studies using recombinant or chimeric antigens and multiepitope peptides method demonstrated very promising results to development of new strategies capable of discriminating recently acquired infections from chronic infection. Real-time PCR and loop-mediated isothermal amplification (LAMP) are two recently developed PCR-based methods with high sensitivity and specificity and could be useful to early diagnosis of infection. Computed tomography, magnetic resonance imaging, nuclear imaging and ultrasonography could be useful, although their results might be not specific alone. This review provides a summary of recent developed methods and also attempts to improve their sensitivity for diagnosis of toxoplasmosis. Serology, molecular and imaging technologies each has their own advantages and limitations which can certainly achieve definitive diagnosis of toxoplasmosis by combining these diagnostic techniques.

Variation in sensitivity, absorption and density of the central rod distribution with eccentricity.

PubMed

Tornow, R P; Stilling, R

1998-01-01

To assess the human rod photopigment distribution and sensitivity with high spatial resolution within the central +/-15 degrees and to compare the results of pigment absorption, sensitivity and rod density distribution (number of rods per square degree). Rod photopigment density distribution was measured with imaging densitometry using a modified Rodenstock scanning laser ophthalmoscope. Dark-adapted sensitivity profiles were measured with green stimuli (17' arc diameter, 1 degrees spacing) using a T ubingen manual perimeter. Sensitivity profiles were plotted on a linear scale and rod photopigment optical density distribution profiles were converted to absorption profiles of the rod photopigment layer. Both the absorption profile of the rod photopigment and the linear sensitivity profile for green stimuli show a minimum at the foveal center and increase steeply with eccentricity. The variation with eccentricity corresponds to the rod density distribution. Rod photopigment absorption profiles, retinal sensitivity profiles, and the rod density distribution are linearly related within the central +/-15 degrees. This is in agreement with theoretical considerations. Both methods, imaging retinal densitometry using a scanning laser ophthalmoscope and dark-adapted perimetry with small green stimuli, are useful for assessing the central rod distribution and sensitivity. However, at present, both methods have limitations. Suggestions for improving the reliability of both methods are given.

Comparison of machine learning methods for classifying mediastinal lymph node metastasis of non-small cell lung cancer from 18F-FDG PET/CT images.

PubMed

Wang, Hongkai; Zhou, Zongwei; Li, Yingci; Chen, Zhonghua; Lu, Peiou; Wang, Wenzhi; Liu, Wanyu; Yu, Lijuan

2017-12-01

This study aimed to compare one state-of-the-art deep learning method and four classical machine learning methods for classifying mediastinal lymph node metastasis of non-small cell lung cancer (NSCLC) from 18 F-FDG PET/CT images. Another objective was to compare the discriminative power of the recently popular PET/CT texture features with the widely used diagnostic features such as tumor size, CT value, SUV, image contrast, and intensity standard deviation. The four classical machine learning methods included random forests, support vector machines, adaptive boosting, and artificial neural network. The deep learning method was the convolutional neural networks (CNN). The five methods were evaluated using 1397 lymph nodes collected from PET/CT images of 168 patients, with corresponding pathology analysis results as gold standard. The comparison was conducted using 10 times 10-fold cross-validation based on the criterion of sensitivity, specificity, accuracy (ACC), and area under the ROC curve (AUC). For each classical method, different input features were compared to select the optimal feature set. Based on the optimal feature set, the classical methods were compared with CNN, as well as with human doctors from our institute. For the classical methods, the diagnostic features resulted in 81~85% ACC and 0.87~0.92 AUC, which were significantly higher than the results of texture features. CNN's sensitivity, specificity, ACC, and AUC were 84, 88, 86, and 0.91, respectively. There was no significant difference between the results of CNN and the best classical method. The sensitivity, specificity, and ACC of human doctors were 73, 90, and 82, respectively. All the five machine learning methods had higher sensitivities but lower specificities than human doctors. The present study shows that the performance of CNN is not significantly different from the best classical methods and human doctors for classifying mediastinal lymph node metastasis of NSCLC from PET/CT images. Because CNN does not need tumor segmentation or feature calculation, it is more convenient and more objective than the classical methods. However, CNN does not make use of the import diagnostic features, which have been proved more discriminative than the texture features for classifying small-sized lymph nodes. Therefore, incorporating the diagnostic features into CNN is a promising direction for future research.

Evaluation of a novel collimator for molecular breast tomosynthesis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gilland, David R.; Welch, Benjamin L.; Lee, Seungjoon

Here, this study investigated a novel gamma camera for molecular breast tomosynthesis (MBT), which is a nuclear breast imaging method that uses limited angle tomography. The camera is equipped with a variable angle, slant-hole (VASH) collimator that allows the camera to remain close to the breast throughout the acquisition. The goal of this study was to evaluate the spatial resolution and count sensitivity of this camera and to compare contrast and contrast-to-noise ratio (CNR) with conventional planar imaging using an experimental breast phantom. Methods The VASH collimator mounts to a commercial gamma camera for breast imaging that uses a pixelatedmore » (3.2 mm), 15 × 20 cm NaI crystal. Spatial resolution was measured in planar images over a range of distances from the collimator (30-100 mm) and a range of slant angles (–25° to 25°) using 99mTc line sources. Spatial resolution was also measured in reconstructed MBT images including in the depth dimension. The images were reconstructed from data acquired over the -25° to 25° angular range using an iterative algorithm adapted to the slant-hole geometry. Sensitivity was measured over the range of slant angles using a disk source. Measured spatial resolution and sensitivity were compared to theoretical values. Contrast and CNR were measured using a breast phantom containing spherical lesions (6.2 mm and 7.8 mm diameter) and positioned over a range of depths in the phantom. The MBT and planar methods had equal scan time, and the count density in the breast phantom data was similar to that in clinical nuclear breast imaging. The MBT method used an iterative reconstruction algorithm combined with a postreconstruction Metz filter. Results The measured spatial resolution in planar images agreed well with theoretical calculations over the range of distances and slant angles. The measured FWHM was 9.7 mm at 50 mm distance. In reconstructed MBT images, the spatial resolution in the depth dimension was approximately 2.2 mm greater than the other two dimensions due to the limited angle data. The measured count sensitivity agreed closely with theory over all slant angles when using a wide energy window. At 0° slant angle, measured sensitivity was 19.7 counts sec -1 μCi -1 with the open energy window and 11.2 counts sec -1 μCi -1 with a 20% wide photopeak window (126 to 154 keV). The measured CNR in the MBT images was significantly greater than in the planar images for all but the lowest CNR cases where the lesion detectability was extremely low for both MBT and planar. The 7.8 mm lesion at 37 mm depth was marginally detectable in the planar image but easily visible in the MBT image. The improved CNR with MBT was due to a large improvement in contrast, which out-weighed the increase in image noise. Conclusion The spatial resolution and count sensitivity measurements with the prototype MBT system matched theoretical calculations, and the measured CNR in breast phantom images was generally greater with the MBT system compared to conventional planar imaging. These results demonstrate the potential of the proposed MBT system to improve lesion detection in nuclear breast imaging.« less

Evaluation of a novel collimator for molecular breast tomosynthesis

DOE PAGES

Gilland, David R.; Welch, Benjamin L.; Lee, Seungjoon; ...

2017-09-06

Here, this study investigated a novel gamma camera for molecular breast tomosynthesis (MBT), which is a nuclear breast imaging method that uses limited angle tomography. The camera is equipped with a variable angle, slant-hole (VASH) collimator that allows the camera to remain close to the breast throughout the acquisition. The goal of this study was to evaluate the spatial resolution and count sensitivity of this camera and to compare contrast and contrast-to-noise ratio (CNR) with conventional planar imaging using an experimental breast phantom. Methods The VASH collimator mounts to a commercial gamma camera for breast imaging that uses a pixelatedmore » (3.2 mm), 15 × 20 cm NaI crystal. Spatial resolution was measured in planar images over a range of distances from the collimator (30-100 mm) and a range of slant angles (–25° to 25°) using 99mTc line sources. Spatial resolution was also measured in reconstructed MBT images including in the depth dimension. The images were reconstructed from data acquired over the -25° to 25° angular range using an iterative algorithm adapted to the slant-hole geometry. Sensitivity was measured over the range of slant angles using a disk source. Measured spatial resolution and sensitivity were compared to theoretical values. Contrast and CNR were measured using a breast phantom containing spherical lesions (6.2 mm and 7.8 mm diameter) and positioned over a range of depths in the phantom. The MBT and planar methods had equal scan time, and the count density in the breast phantom data was similar to that in clinical nuclear breast imaging. The MBT method used an iterative reconstruction algorithm combined with a postreconstruction Metz filter. Results The measured spatial resolution in planar images agreed well with theoretical calculations over the range of distances and slant angles. The measured FWHM was 9.7 mm at 50 mm distance. In reconstructed MBT images, the spatial resolution in the depth dimension was approximately 2.2 mm greater than the other two dimensions due to the limited angle data. The measured count sensitivity agreed closely with theory over all slant angles when using a wide energy window. At 0° slant angle, measured sensitivity was 19.7 counts sec -1 μCi -1 with the open energy window and 11.2 counts sec -1 μCi -1 with a 20% wide photopeak window (126 to 154 keV). The measured CNR in the MBT images was significantly greater than in the planar images for all but the lowest CNR cases where the lesion detectability was extremely low for both MBT and planar. The 7.8 mm lesion at 37 mm depth was marginally detectable in the planar image but easily visible in the MBT image. The improved CNR with MBT was due to a large improvement in contrast, which out-weighed the increase in image noise. Conclusion The spatial resolution and count sensitivity measurements with the prototype MBT system matched theoretical calculations, and the measured CNR in breast phantom images was generally greater with the MBT system compared to conventional planar imaging. These results demonstrate the potential of the proposed MBT system to improve lesion detection in nuclear breast imaging.« less

2D-3D registration using gradient-based MI for image guided surgery systems

NASA Astrophysics Data System (ADS)

Yim, Yeny; Chen, Xuanyi; Wakid, Mike; Bielamowicz, Steve; Hahn, James

2011-03-01

Registration of preoperative CT data to intra-operative video images is necessary not only to compare the outcome of the vocal fold after surgery with the preplanned shape but also to provide the image guidance for fusion of all imaging modalities. We propose a 2D-3D registration method using gradient-based mutual information. The 3D CT scan is aligned to 2D endoscopic images by finding the corresponding viewpoint between the real camera for endoscopic images and the virtual camera for CT scans. Even though mutual information has been successfully used to register different imaging modalities, it is difficult to robustly register the CT rendered image to the endoscopic image due to varying light patterns and shape of the vocal fold. The proposed method calculates the mutual information in the gradient images as well as original images, assigning more weight to the high gradient regions. The proposed method can emphasize the effect of vocal fold and allow a robust matching regardless of the surface illumination. To find the viewpoint with maximum mutual information, a downhill simplex method is applied in a conditional multi-resolution scheme which leads to a less-sensitive result to local maxima. To validate the registration accuracy, we evaluated the sensitivity to initial viewpoint of preoperative CT. Experimental results showed that gradient-based mutual information provided robust matching not only for two identical images with different viewpoints but also for different images acquired before and after surgery. The results also showed that conditional multi-resolution scheme led to a more accurate registration than single-resolution.

Highly accelerated acquisition and homogeneous image reconstruction with rotating RF coil array at 7T-A phantom based study.

PubMed

Li, Mingyan; Zuo, Zhentao; Jin, Jin; Xue, Rong; Trakic, Adnan; Weber, Ewald; Liu, Feng; Crozier, Stuart

2014-03-01

Parallel imaging (PI) is widely used for imaging acceleration by means of coil spatial sensitivities associated with phased array coils (PACs). By employing a time-division multiplexing technique, a single-channel rotating radiofrequency coil (RRFC) provides an alternative method to reduce scan time. Strategically combining these two concepts could provide enhanced acceleration and efficiency. In this work, the imaging acceleration ability and homogeneous image reconstruction strategy of 4-element rotating radiofrequency coil array (RRFCA) was numerically investigated and experimental validated at 7T with a homogeneous phantom. Each coil of RRFCA was capable of acquiring a large number of sensitivity profiles, leading to a better acceleration performance illustrated by the improved geometry-maps that have lower maximum values and more uniform distributions compared to 4- and 8-element stationary arrays. A reconstruction algorithm, rotating SENSitivity Encoding (rotating SENSE), was proposed to provide image reconstruction. Additionally, by optimally choosing the angular sampling positions and transmit profiles under the rotating scheme, phantom images could be faithfully reconstructed. The results indicate that, the proposed technique is able to provide homogeneous reconstructions with overall higher and more uniform signal-to-noise ratio (SNR) distributions at high reduction factors. It is hoped that, by employing the high imaging acceleration and homogeneous imaging reconstruction ability of RRFCA, the proposed method will facilitate human imaging for ultra high field MRI. Copyright © 2013 Elsevier Inc. All rights reserved.

Radionuclide Methods and Instrumentation for Breast Cancer Detection and Diagnosis

PubMed Central

Surti, Suleman

2013-01-01

Breast cancer mammography is a well-acknowledged technique for patient screening due to its high sensitivity. However, in addition to its low specificity the sensitivity of mammography is limited when imaging patients with dense breasts. Radionuclide imaging techniques, such as coincidence photon-based positron emission tomography and single photon emission computed tomography or scintimammography, can play a role in assisting screening of such patients. Radionuclide techniques can also be useful in assessing treatment response of patients with breast cancer to therapy, and staging of patients to diagnose the disease extent. However, the performance of these imaging modalities is generally limited because of the poor spatial resolution and sensitivity of the commercially available multipurpose imaging systems. Here, we describe some of the dedicated imaging systems (positron emission mammography [PEM] and breast-specific gamma imaging [BSGI]) that have been developed both commercially and in research laboratories for radionuclide imaging of breast cancer. Clinical studies with dedicated PEM scanners show improved sensitivity to detecting cancer in patients when using PEM in conjunction with additional imaging modalities, such as magnetic resonance imaging or mammography or both, as well as improved disease staging that can have an effect on surgical planning. High-resolution BSGI systems are more widely available commercially and several clinical studies have shown very high sensitivity and specificity in detecting cancer in high-risk patients. Further development of dedicated PEM and BSGI systems is ongoing, promising further expansion of radionuclide imaging techniques in the realm of breast cancer detection and treatment. PMID:23725989

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Jianfei; Wang, Shijun; Turkbey, Evrim B.

Purpose: Renal calculi are common extracolonic incidental findings on computed tomographic colonography (CTC). This work aims to develop a fully automated computer-aided diagnosis system to accurately detect renal calculi on CTC images. Methods: The authors developed a total variation (TV) flow method to reduce image noise within the kidneys while maintaining the characteristic appearance of renal calculi. Maximally stable extremal region (MSER) features were then calculated to robustly identify calculi candidates. Finally, the authors computed texture and shape features that were imported to support vector machines for calculus classification. The method was validated on a dataset of 192 patients andmore » compared to a baseline approach that detects calculi by thresholding. The authors also compared their method with the detection approaches using anisotropic diffusion and nonsmoothing. Results: At a false positive rate of 8 per patient, the sensitivities of the new method and the baseline thresholding approach were 69% and 35% (p < 1e − 3) on all calculi from 1 to 433 mm{sup 3} in the testing dataset. The sensitivities of the detection methods using anisotropic diffusion and nonsmoothing were 36% and 0%, respectively. The sensitivity of the new method increased to 90% if only larger and more clinically relevant calculi were considered. Conclusions: Experimental results demonstrated that TV-flow and MSER features are efficient means to robustly and accurately detect renal calculi on low-dose, high noise CTC images. Thus, the proposed method can potentially improve diagnosis.« less

A geometrical defect detection method for non-silicon MEMS part based on HU moment invariants of skeleton image

NASA Astrophysics Data System (ADS)

Cheng, Xu; Jin, Xin; Zhang, Zhijing; Lu, Jun

2014-01-01

In order to improve the accuracy of geometrical defect detection, this paper presented a method based on HU moment invariants of skeleton image. This method have four steps: first of all, grayscale images of non-silicon MEMS parts are collected and converted into binary images, secondly, skeletons of binary images are extracted using medialaxis- transform method, and then HU moment invariants of skeleton images are calculated, finally, differences of HU moment invariants between measured parts and qualified parts are obtained to determine whether there are geometrical defects. To demonstrate the availability of this method, experiments were carried out between skeleton images and grayscale images, and results show that: when defects of non-silicon MEMS part are the same, HU moment invariants of skeleton images are more sensitive than that of grayscale images, and detection accuracy is higher. Therefore, this method can more accurately determine whether non-silicon MEMS parts qualified or not, and can be applied to nonsilicon MEMS part detection system.

Theoretical evaluation of accuracy in position and size of brain activity obtained by near-infrared topography

NASA Astrophysics Data System (ADS)

Kawaguchi, Hiroshi; Hayashi, Toshiyuki; Kato, Toshinori; Okada, Eiji

2004-06-01

Near-infrared (NIR) topography can obtain a topographical distribution of the activated region in the brain cortex. Near-infrared light is strongly scattered in the head, and the volume of tissue sampled by a source-detector pair on the head surface is broadly distributed in the brain. This scattering effect results in poor resolution and contrast in the topographic image of the brain activity. In this study, a one-dimensional distribution of absorption change in a head model is calculated by mapping and reconstruction methods to evaluate the effect of the image reconstruction algorithm and the interval of measurement points for topographic imaging on the accuracy of the topographic image. The light propagation in the head model is predicted by Monte Carlo simulation to obtain the spatial sensitivity profile for a source-detector pair. The measurement points are one-dimensionally arranged on the surface of the model, and the distance between adjacent measurement points is varied from 4 mm to 28 mm. Small intervals of the measurement points improve the topographic image calculated by both the mapping and reconstruction methods. In the conventional mapping method, the limit of the spatial resolution depends upon the interval of the measurement points and spatial sensitivity profile for source-detector pairs. The reconstruction method has advantages over the mapping method which improve the results of one-dimensional analysis when the interval of measurement points is less than 12 mm. The effect of overlapping of spatial sensitivity profiles indicates that the reconstruction method may be effective to improve the spatial resolution of a two-dimensional reconstruction of topographic image obtained with larger interval of measurement points. Near-infrared topography with the reconstruction method potentially obtains an accurate distribution of absorption change in the brain even if the size of absorption change is less than 10 mm.

Seismic Imaging of VTI, HTI and TTI based on Adjoint Methods

NASA Astrophysics Data System (ADS)

Rusmanugroho, H.; Tromp, J.

2014-12-01

Recent studies show that isotropic seismic imaging based on adjoint method reduces low-frequency artifact caused by diving waves, which commonly occur in two-wave wave-equation migration, such as Reverse Time Migration (RTM). Here, we derive new expressions of sensitivity kernels for Vertical Transverse Isotropy (VTI) using the Thomsen parameters (ɛ, δ, γ) plus the P-, and S-wave speeds (α, β) as well as via the Chen & Tromp (GJI 2005) parameters (A, C, N, L, F). For Horizontal Transverse Isotropy (HTI), these parameters depend on an azimuthal angle φ, where the tilt angle θ is equivalent to 90°, and for Tilted Transverse Isotropy (TTI), these parameters depend on both the azimuth and tilt angles. We calculate sensitivity kernels for each of these two approaches. Individual kernels ("images") are numerically constructed based on the interaction between the regular and adjoint wavefields in smoothed models which are in practice estimated through Full-Waveform Inversion (FWI). The final image is obtained as a result of summing all shots, which are well distributed to sample the target model properly. The impedance kernel, which is a sum of sensitivity kernels of density and the Thomsen or Chen & Tromp parameters, looks crisp and promising for seismic imaging. The other kernels suffer from low-frequency artifacts, similar to traditional seismic imaging conditions. However, all sensitivity kernels are important for estimating the gradient of the misfit function, which, in combination with a standard gradient-based inversion algorithm, is used to minimize the objective function in FWI.

A New Pulse Pileup Rejection Method Based on Position Shift Identification

NASA Astrophysics Data System (ADS)

Gu, Z.; Prout, D. L.; Taschereau, R.; Bai, B.; Chatziioannou, A. F.

2016-02-01

Pulse pileup events degrade the signal-to-noise ratio (SNR) of nuclear medicine data. When such events occur in multiplexed detectors, they cause spatial misposition, energy spectrum distortion and degraded timing resolution, which leads to image artifacts. Pulse pileup is pronounced in PETbox4, a bench top PET scanner dedicated to high sensitivity and high resolution imaging of mice. In that system, the combination of high absolute sensitivity, long scintillator decay time (BGO) and highly multiplexed electronics lead to a significant fraction of pulse pileup, reached at lower total activity than for comparable instruments. In this manuscript, a new pulse pileup rejection method named position shift rejection (PSR) is introduced. The performance of PSR is compared with a conventional leading edge rejection (LER) method and with no pileup rejection implemented (NoPR). A comprehensive digital pulse library was developed for objective evaluation and optimization of the PSR and LER, in which pulse waveforms were directly recorded from real measurements exactly representing the signals to be processed. Physical measurements including singles event acquisition, peak system sensitivity and NEMA NU-4 image quality phantom were also performed in the PETbox4 system to validate and compare the different pulse pile-up rejection methods. The evaluation of both physical measurements and model pulse trains demonstrated that the new PSR performs more accurate pileup event identification and avoids erroneous rejection of valid events. For the PETbox4 system, this improvement leads to a significant recovery of sensitivity at low count rates, amounting to about 1/4th of the expected true coincidence events, compared to the LER method. Furthermore, with the implementation of PSR, optimal image quality can be achieved near the peak noise equivalent count rate (NECR).

The Research of Feature Extraction Method of Liver Pathological Image Based on Multispatial Mapping and Statistical Properties

PubMed Central

Liu, Huiling; Xia, Bingbing; Yi, Dehui

2016-01-01

We propose a new feature extraction method of liver pathological image based on multispatial mapping and statistical properties. For liver pathological images of Hematein Eosin staining, the image of R and B channels can reflect the sensitivity of liver pathological images better, while the entropy space and Local Binary Pattern (LBP) space can reflect the texture features of the image better. To obtain the more comprehensive information, we map liver pathological images to the entropy space, LBP space, R space, and B space. The traditional Higher Order Local Autocorrelation Coefficients (HLAC) cannot reflect the overall information of the image, so we propose an average correction HLAC feature. We calculate the statistical properties and the average gray value of pathological images and then update the current pixel value as the absolute value of the difference between the current pixel gray value and the average gray value, which can be more sensitive to the gray value changes of pathological images. Lastly the HLAC template is used to calculate the features of the updated image. The experiment results show that the improved features of the multispatial mapping have the better classification performance for the liver cancer. PMID:27022407

MOCC: A Fast and Robust Correlation-Based Method for Interest Point Matching under Large Scale Changes

NASA Astrophysics Data System (ADS)

Zhao, Feng; Huang, Qingming; Wang, Hao; Gao, Wen

2010-12-01

Similarity measures based on correlation have been used extensively for matching tasks. However, traditional correlation-based image matching methods are sensitive to rotation and scale changes. This paper presents a fast correlation-based method for matching two images with large rotation and significant scale changes. Multiscale oriented corner correlation (MOCC) is used to evaluate the degree of similarity between the feature points. The method is rotation invariant and capable of matching image pairs with scale changes up to a factor of 7. Moreover, MOCC is much faster in comparison with the state-of-the-art matching methods. Experimental results on real images show the robustness and effectiveness of the proposed method.

Time-lapse imaging assay using the BioStation CT: A sensitive drug-screening method for three-dimensional cell culture

PubMed Central

Sakamoto, Ruriko; Rahman, M Mamunur; Shimomura, Manami; Itoh, Manabu; Nakatsura, Tetsuya

2015-01-01

Three-dimensional (3D) cell culture is beneficial for physiological studies of tumor cells, due to its potential to deliver a high quantity of cell culture information that is representative of the cancer microenvironment and predictive of drug responses in vivo. Currently, gel-associated or matrix-associated 3D cell culture is comprised of intricate procedures that often result in experimental complexity. Therefore, we developed an innovative anti-cancer drug sensitivity screening technique for 3D cell culture on NanoCulture Plates (NCP) by employing the imaging device BioStation CT. Here, we showed that the human breast cancer cell lines BT474 and T47D form multicellular spheroids on NCP plates and compared their sensitivity to the anti-cancer drugs trastuzumab and paclitaxel using the BioStation CT. The anticancer drugs reduced spheroid migration velocity and suppressed spheroid fusion. In addition, primary cells derived from the human breast cancer tissues B58 and B61 grown on NCP plates also exhibited similar drug sensitivity. These results were in good agreement with the conventional assay method using ATP quantification. We confirmed the antitumor effects of the drugs on cells seeded in 96-well plates using the BioStation CT imaging technique. We expect this method to be useful in research for new antitumor agents and for drug sensitivity tests in individually-tailored cancer treatments. PMID:25865675

Matching CCD images to a stellar catalog using locality-sensitive hashing

NASA Astrophysics Data System (ADS)

Liu, Bo; Yu, Jia-Zong; Peng, Qing-Yu

2018-02-01

The usage of a subset of observed stars in a CCD image to find their corresponding matched stars in a stellar catalog is an important issue in astronomical research. Subgraph isomorphic-based algorithms are the most widely used methods in star catalog matching. When more subgraph features are provided, the CCD images are recognized better. However, when the navigation feature database is large, the method requires more time to match the observing model. To solve this problem, this study investigates further and improves subgraph isomorphic matching algorithms. We present an algorithm based on a locality-sensitive hashing technique, which allocates quadrilateral models in the navigation feature database into different hash buckets and reduces the search range to the bucket in which the observed quadrilateral model is located. Experimental results indicate the effectivity of our method.

Particle swarm optimization method for small retinal vessels detection on multiresolution fundus images.

PubMed

Khomri, Bilal; Christodoulidis, Argyrios; Djerou, Leila; Babahenini, Mohamed Chaouki; Cheriet, Farida

2018-05-01

Retinal vessel segmentation plays an important role in the diagnosis of eye diseases and is considered as one of the most challenging tasks in computer-aided diagnosis (CAD) systems. The main goal of this study was to propose a method for blood-vessel segmentation that could deal with the problem of detecting vessels of varying diameters in high- and low-resolution fundus images. We proposed to use the particle swarm optimization (PSO) algorithm to improve the multiscale line detection (MSLD) method. The PSO algorithm was applied to find the best arrangement of scales in the MSLD method and to handle the problem of multiscale response recombination. The performance of the proposed method was evaluated on two low-resolution (DRIVE and STARE) and one high-resolution fundus (HRF) image datasets. The data include healthy (H) and diabetic retinopathy (DR) cases. The proposed approach improved the sensitivity rate against the MSLD by 4.7% for the DRIVE dataset and by 1.8% for the STARE dataset. For the high-resolution dataset, the proposed approach achieved 87.09% sensitivity rate, whereas the MSLD method achieves 82.58% sensitivity rate at the same specificity level. When only the smallest vessels were considered, the proposed approach improved the sensitivity rate by 11.02% and by 4.42% for the healthy and the diabetic cases, respectively. Integrating the proposed method in a comprehensive CAD system for DR screening would allow the reduction of false positives due to missed small vessels, misclassified as red lesions. (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

Method to improve cancerous lesion detection sensitivity in a dedicated dual-head scintimammography system

DOEpatents

Kieper, Douglas Arthur [Seattle, WA; Majewski, Stanislaw [Morgantown, WV; Welch, Benjamin L [Hampton, VA

2012-07-03

An improved method for enhancing the contrast between background and lesion areas of a breast undergoing dual-head scintimammographic examination comprising: 1) acquiring a pair of digital images from a pair of small FOV or mini gamma cameras compressing the breast under examination from opposing sides; 2) inverting one of the pair of images to align or co-register with the other of the images to obtain co-registered pixel values; 3) normalizing the pair of images pixel-by-pixel by dividing pixel values from each of the two acquired images and the co-registered image by the average count per pixel in the entire breast area of the corresponding detector; and 4) multiplying the number of counts in each pixel by the value obtained in step 3 to produce a normalization enhanced two dimensional contrast map. This enhanced (increased contrast) contrast map enhances the visibility of minor local increases (uptakes) of activity over the background and therefore improves lesion detection sensitivity, especially of small lesions.

Method to improve cancerous lesion detection sensitivity in a dedicated dual-head scintimammography system

DOEpatents

Kieper, Douglas Arthur [Newport News, VA; Majewski, Stanislaw [Yorktown, VA; Welch, Benjamin L [Hampton, VA

2008-10-28

An improved method for enhancing the contrast between background and lesion areas of a breast undergoing dual-head scintimammographic examination comprising: 1) acquiring a pair of digital images from a pair of small FOV or mini gamma cameras compressing the breast under examination from opposing sides; 2) inverting one of the pair of images to align or co-register with the other of the images to obtain co-registered pixel values; 3) normalizing the pair of images pixel-by-pixel by dividing pixel values from each of the two acquired images and the co-registered image by the average count per pixel in the entire breast area of the corresponding detector; and 4) multiplying the number of counts in each pixel by the value obtained in step 3 to produce a normalization enhanced two dimensional contrast map. This enhanced (increased contrast) contrast map enhances the visibility of minor local increases (uptakes) of activity over the background and therefore improves lesion detection sensitivity, especially of small lesions.

Combined FLIM and reflectance confocal microscopy for epithelial imaging

NASA Astrophysics Data System (ADS)

Jabbour, Joey M.; Cheng, Shuna; Shrestha, Sebina; Malik, Bilal; Jo, Javier A.; Applegate, Brian; Maitland, Kristen C.

2012-03-01

Current methods for detection of oral cancer lack the ability to delineate between normal and precancerous tissue with adequate sensitivity and specificity. The usual diagnostic mechanism involves visual inspection and palpation followed by tissue biopsy and histopathology, a process both invasive and time-intensive. A more sensitive and objective screening method can greatly facilitate the overall process of detection of early cancer. To this end, we present a multimodal imaging system with fluorescence lifetime imaging (FLIM) for wide field of view guidance and reflectance confocal microscopy for sub-cellular resolution imaging of epithelial tissue. Moving from a 12 x 12 mm2 field of view with 157 ìm lateral resolution using FLIM to 275 x 200 μm2 with lateral resolution of 2.2 μm using confocal microscopy, hamster cheek pouch model is imaged both in vivo and ex vivo. The results indicate that our dual modality imaging system can identify and distinguish between different tissue features, and, therefore, can potentially serve as a guide in early oral cancer detection..

Towards pH-sensitive imaging of small animals with photon-counting difference diffuse fluorescence tomography

NASA Astrophysics Data System (ADS)

Li, Jiao; Wang, Xin; Yi, Xi; Zhang, Limin; Zhou, Zhongxing; Zhao, Huijuan; Gao, Feng

2012-09-01

The importance of cellular pH has been shown clearly in the study of cell activity, pathological feature, and drug metabolism. Monitoring pH changes of living cells and imaging the regions with abnormal pH-values, in vivo, could provide invaluable physiological and pathological information for the research of the cell biology, pharmacokinetics, diagnostics, and therapeutics of certain diseases such as cancer. Naturally, pH-sensitive fluorescence imaging of bulk tissues has been attracting great attentions from the realm of near infrared diffuse fluorescence tomography (DFT). Herein, the feasibility of quantifying pH-induced fluorescence changes in turbid medium is investigated using a continuous-wave difference-DFT technique that is based on the specifically designed computed tomography-analogous photon counting system and the Born normalized difference image reconstruction scheme. We have validated the methodology using two-dimensional imaging experiments on a small-animal-sized phantom, embedding an inclusion with varying pH-values. The results show that the proposed approach can accurately localize the target with a quantitative resolution to pH-sensitive variation of the fluorescent yield, and might provide a promising alternative method of pH-sensitive fluorescence imaging in addition to the fluorescence-lifetime imaging.

SYMPOSIUM ON MULTIMODALITY CARDIOVASCULAR MOLECULAR IMAGING IMAGING TECHNOLOGY - PART 2

PubMed Central

de Kemp, Robert A.; Epstein, Frederick H.; Catana, Ciprian; Tsui, Benjamin M.W.; Ritman, Erik L.

2013-01-01

Rationale The ability to trace or identify specific molecules within a specific anatomic location provides insight into metabolic pathways, tissue components and tracing of solute transport mechanisms. With the increasing use of small animals for research such imaging must have sufficiently high spatial resolution to allow anatomic localization as well as sufficient specificity and sensitivity to provide an accurate description of the molecular distribution and concentration. Methods Imaging methods based on electromagnetic radiation, such as PET, SPECT, MRI and CT, are increasingly applicable due to recent advances in novel scanner hardware, image reconstruction software and availability of novel molecules which have enhanced sensitivity in these methodologies. Results Micro-PET has been advanced by development of detector arrays that provide higher resolution and positron emitting elements that allow new molecular tracers to be labeled. Micro-MRI has been improved in terms of spatial resolution and sensitivity by increased magnet field strength and development of special purpose coils and associated scan protocols. Of particular interest is the associated ability to image local mechanical function and solute transport processes which can be directly related to the molecular information. This is further strengthened by the synergistic integration of the PET with MRI. Micro-SPECT has been improved by use of coded aperture imaging approaches as well as image reconstruction algorithms which can better deal with the photon limited scan data. The limited spatial resolution can be partially overcome by integrating the SPECT with CT. Micro-CT by itself provides exquisite spatial resolution of anatomy, but recent developments of high spatial resolution photon counting and spectrally-sensitive imaging arrays, combined with x-ray optical devices, have promise for actual molecular identification by virtue of the chemical bond lengths of molecules, especially of bio-polymers. Conclusion With the increasing use of small animals for evaluating new clinical imaging techniques as well as providing increased insights into patho-physiological phenomena, the availability of improved detection systems, scanning protocols and associated software, the repertoire of molecular imaging is greatly increased in sensitivity and specificity. PMID:20457793

Phase retrieval using regularization method in intensity correlation imaging

NASA Astrophysics Data System (ADS)

Li, Xiyu; Gao, Xin; Tang, Jia; Lu, Changming; Wang, Jianli; Wang, Bin

2014-11-01

Intensity correlation imaging(ICI) method can obtain high resolution image with ground-based low precision mirrors, in the imaging process, phase retrieval algorithm should be used to reconstituted the object's image. But the algorithm now used(such as hybrid input-output algorithm) is sensitive to noise and easy to stagnate. However the signal-to-noise ratio of intensity interferometry is low especially in imaging astronomical objects. In this paper, we build the mathematical model of phase retrieval and simplified it into a constrained optimization problem of a multi-dimensional function. New error function was designed by noise distribution and prior information using regularization method. The simulation results show that the regularization method can improve the performance of phase retrieval algorithm and get better image especially in low SNR condition

Three-dimensional Fréchet sensitivity kernels for electromagnetic wave propagation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Strickland, C. E.; Johnson, T. C.; Odom, R. I.

2015-08-28

Electromagnetic imaging methods are useful tools for monitoring subsurface changes in pore-fluid content and the associated changes in electrical permittivity and conductivity. The most common method for georadar tomography uses a high frequency ray-theoretic approximation that is valid when material variations are sufficiently small relative to the wavelength of the propagating wave. Georadar methods, however, often utilize electromagnetic waves that propagate within heterogeneous media at frequencies where ray theory may not be applicable. In this paper we describe the 3-D Fréchet sensitivity kernels for EM wave propagation. Various data functional types are formulated that consider all three components of themore » electric wavefield and incorporate near-, intermediate-, and far-field contributions. We show that EM waves exhibit substantial variations for different relative source-receiver component orientations. The 3-D sensitivities also illustrate out-of-plane effects that are not captured in 2-D sensitivity kernels and can influence results obtained using 2-D inversion methods to image structures that are in reality 3-D.« less

Deep Constrained Siamese Hash Coding Network and Load-Balanced Locality-Sensitive Hashing for Near Duplicate Image Detection.

PubMed

Hu, Weiming; Fan, Yabo; Xing, Junliang; Sun, Liang; Cai, Zhaoquan; Maybank, Stephen

2018-09-01

We construct a new efficient near duplicate image detection method using a hierarchical hash code learning neural network and load-balanced locality-sensitive hashing (LSH) indexing. We propose a deep constrained siamese hash coding neural network combined with deep feature learning. Our neural network is able to extract effective features for near duplicate image detection. The extracted features are used to construct a LSH-based index. We propose a load-balanced LSH method to produce load-balanced buckets in the hashing process. The load-balanced LSH significantly reduces the query time. Based on the proposed load-balanced LSH, we design an effective and feasible algorithm for near duplicate image detection. Extensive experiments on three benchmark data sets demonstrate the effectiveness of our deep siamese hash encoding network and load-balanced LSH.

Multiphoton luminescent graphene quantum dots for in vivo tracking of human adipose-derived stem cells

NASA Astrophysics Data System (ADS)

Kim, Jin; Song, Sung Ho; Jin, Yoonhee; Park, Hyun-Ji; Yoon, Hyewon; Jeon, Seokwoo; Cho, Seung-Woo

2016-04-01

The applicability of graphene quantum dots (GQDs) for the in vitro and in vivo live imaging and tracking of different types of human stem cells is investigated. GQDs synthesized by the modified graphite intercalated compound method show efficient cellular uptake with improved biocompatibility and highly sensitive optical properties, indicating their feasibility as a bio-imaging probe for stem cell therapy.The applicability of graphene quantum dots (GQDs) for the in vitro and in vivo live imaging and tracking of different types of human stem cells is investigated. GQDs synthesized by the modified graphite intercalated compound method show efficient cellular uptake with improved biocompatibility and highly sensitive optical properties, indicating their feasibility as a bio-imaging probe for stem cell therapy. Electronic supplementary information (ESI) available: Additional results. See DOI: 10.1039/c6nr02143c

Magnetic Resonance Imaging of Liver Metastasis.

PubMed

Karaosmanoglu, Ali Devrim; Onur, Mehmet Ruhi; Ozmen, Mustafa Nasuh; Akata, Deniz; Karcaaltincaba, Musturay

2016-12-01

Liver magnetic resonance imaging (MRI) is becoming the gold standard in liver metastasis detection and treatment response assessment. The most sensitive magnetic resonance sequences are diffusion-weighted images and hepatobiliary phase images after Gd-EOB-DTPA. Peripheral ring enhancement, diffusion restriction, and hypointensity on hepatobiliary phase images are hallmarks of liver metastases. In patients with normal ultrasonography, computed tomography (CT), and positron emission tomography (PET)-CT findings and high clinical suspicion of metastasis, MRI should be performed for diagnosis of unseen metastasis. In melanoma, colon cancer, and neuroendocrine tumor metastases, MRI allows confident diagnosis of treatment-related changes in liver and enables differential diagnosis from primary liver tumors. Focal nodular hyperplasia-like nodules in patients who received platinum-based chemotherapy, hypersteatosis, and focal fat can mimic metastasis. In cancer patients with fatty liver, MRI should be preferred to CT. Although the first-line imaging for metastases is CT, MRI can be used as a problem-solving method. MRI may be used as the first-line method in patients who would undergo curative surgery or metastatectomy. Current limitation of MRI is low sensitivity for metastasis smaller than 3mm. MRI fingerprinting, glucoCEST MRI, and PET-MRI may allow simpler and more sensitive diagnosis of liver metastasis. Copyright © 2016 Elsevier Inc. All rights reserved.

A review of optimization and quantification techniques for chemical exchange saturation transfer (CEST) MRI toward sensitive in vivo imaging

PubMed Central

Guo, Yingkun; Zheng, Hairong; Sun, Phillip Zhe

2015-01-01

Chemical exchange saturation transfer (CEST) MRI is a versatile imaging method that probes the chemical exchange between bulk water and exchangeable protons. CEST imaging indirectly detects dilute labile protons via bulk water signal changes following selective saturation of exchangeable protons, which offers substantial sensitivity enhancement and has sparked numerous biomedical applications. Over the past decade, CEST imaging techniques have rapidly evolved due to contributions from multiple domains, including the development of CEST mathematical models, innovative contrast agent designs, sensitive data acquisition schemes, efficient field inhomogeneity correction algorithms, and quantitative CEST (qCEST) analysis. The CEST system that underlies the apparent CEST-weighted effect, however, is complex. The experimentally measurable CEST effect depends not only on parameters such as CEST agent concentration, pH and temperature, but also on relaxation rate, magnetic field strength and more importantly, experimental parameters including repetition time, RF irradiation amplitude and scheme, and image readout. Thorough understanding of the underlying CEST system using qCEST analysis may augment the diagnostic capability of conventional imaging. In this review, we provide a concise explanation of CEST acquisition methods and processing algorithms, including their advantages and limitations, for optimization and quantification of CEST MRI experiments. PMID:25641791

Nanotechnology: a promising method for oral cancer detection and diagnosis.

PubMed

Chen, Xiao-Jie; Zhang, Xue-Qiong; Liu, Qi; Zhang, Jing; Zhou, Gang

2018-06-11

Oral cancer is a common and aggressive cancer with high morbidity, mortality, and recurrence rate globally. Early detection is of utmost importance for cancer prevention and disease management. Currently, tissue biopsy remains the gold standard for oral cancer diagnosis, but it is invasive, which may cause patient discomfort. The application of traditional noninvasive methods-such as vital staining, exfoliative cytology, and molecular imaging-is limited by insufficient sensitivity and specificity. Thus, there is an urgent need for exploring noninvasive, highly sensitive, and specific diagnostic techniques. Nano detection systems are known as new emerging noninvasive strategies that bring the detection sensitivity of biomarkers to nano-scale. Moreover, compared to current imaging contrast agents, nanoparticles are more biocompatible, easier to synthesize, and able to target specific surface molecules. Nanoparticles generate localized surface plasmon resonances at near-infrared wavelengths, providing higher image contrast and resolution. Therefore, using nano-based techniques can help clinicians to detect and better monitor diseases during different phases of oral malignancy. Here, we review the progress of nanotechnology-based methods in oral cancer detection and diagnosis.

Multiwavelet grading of prostate pathological images

NASA Astrophysics Data System (ADS)

Soltanian-Zadeh, Hamid; Jafari-Khouzani, Kourosh

2002-05-01

We have developed image analysis methods to automatically grade pathological images of prostate. The proposed method generates Gleason grades to images, where each image is assigned a grade between 1 and 5. This is done using features extracted from multiwavelet transformations. We extract energy and entropy features from submatrices obtained in the decomposition. Next, we apply a k-NN classifier to grade the image. To find optimal multiwavelet basis, preprocessing, and classifier, we use features extracted by different multiwavelets with either critically sampled preprocessing or repeated row preprocessing and different k-NN classifiers and compare their performances, evaluated by total misclassification rate (TMR). To evaluate sensitivity to noise, we add white Gaussian noise to images and compare the results (TMR's). We applied proposed methods to 100 images. We evaluated the first and second levels of decomposition using Geronimo, Hardin, and Massopust (GHM), Chui and Lian (CL), and Shen (SA4) multiwavelets. We also evaluated k-NN classifier for k=1,2,3,4,5. Experimental results illustrate that first level of decomposition is quite noisy. They also show that critically sampled preprocessing outperforms repeated row preprocessing and has less sensitivity to noise. Finally, comparison studies indicate that SA4 multiwavelet and k-NN classifier (k=1) generates optimal results (with smallest TMR of 3%).

Motion Artefacts in MRI: a Complex Problem with Many Partial Solutions

PubMed Central

Zaitsev, Maxim; Maclaren, Julian.; Herbst, Michael

2015-01-01

Subject motion during magnetic resonance imaging (MRI) has been problematic since its introduction as a clinical imaging modality. While sensitivity to particle motion or blood flow can be used to provide useful image contrast, bulk motion presents a considerable problem in the majority of clinical applications. It is one of the most frequent sources of artefacts. Over 30 years of research have produced numerous methods to mitigate or correct for motion artefacts, but no single method can be applied in all imaging situations. Instead, a ‘toolbox’ of methods exists, where each tool is suitable for some tasks, but not for others. This article reviews the origins of motion artefacts and presents current mitigation and correction methods. In some imaging situations, the currently available motion correction tools are highly effective; in other cases, appropriate tools still need to be developed. It seems likely that this multifaceted approach will be what eventually solves the motion sensitivity problem in MRI, rather than a single solution that is effective in all situations. This review places a strong emphasis on explaining the physics behind the occurrence of such artefacts, with the aim of aiding artefact detection and mitigation in particular clinical situations. PMID:25630632

Motion artifacts in MRI: A complex problem with many partial solutions.

PubMed

Zaitsev, Maxim; Maclaren, Julian; Herbst, Michael

2015-10-01

Subject motion during magnetic resonance imaging (MRI) has been problematic since its introduction as a clinical imaging modality. While sensitivity to particle motion or blood flow can be used to provide useful image contrast, bulk motion presents a considerable problem in the majority of clinical applications. It is one of the most frequent sources of artifacts. Over 30 years of research have produced numerous methods to mitigate or correct for motion artifacts, but no single method can be applied in all imaging situations. Instead, a "toolbox" of methods exists, where each tool is suitable for some tasks, but not for others. This article reviews the origins of motion artifacts and presents current mitigation and correction methods. In some imaging situations, the currently available motion correction tools are highly effective; in other cases, appropriate tools still need to be developed. It seems likely that this multifaceted approach will be what eventually solves the motion sensitivity problem in MRI, rather than a single solution that is effective in all situations. This review places a strong emphasis on explaining the physics behind the occurrence of such artifacts, with the aim of aiding artifact detection and mitigation in particular clinical situations. © 2015 Wiley Periodicals, Inc.

Sensitive elemental detection using microwave-assisted laser-induced breakdown imaging

NASA Astrophysics Data System (ADS)

Iqbal, Adeel; Sun, Zhiwei; Wall, Matthew; Alwahabi, Zeyad T.

2017-10-01

This study reports a sensitive spectroscopic method for quantitative elemental detection by manipulating the temporal and spatial parameters of laser-induced plasma. The method was tested for indium detection in solid samples, in which laser ablation was used to generate a tiny plasma. The lifetime of the laser-induced plasma can be extended to hundreds of microseconds using microwave injection to remobilize the electrons. In this novel method, temporal integrated signal of indium emission was significantly enhanced. Meanwhile, the projected detectable area of the excited indium atoms was also significantly improved using an interference-, instead of diffraction-, based technique, achieved by directly imaging microwave-enhanced plasma through a novel narrow-bandpass filter, exactly centered at the indium emission line. Quantitative laser-induce breakdown spectroscopy was also recorded simultaneously with the new imaging method. The intensities recorded from both methods exhibit very good mutual linear relationship. The detection intensity was improved to 14-folds because of the combined improvements in the plasma lifetime and the area of detection.

Adaptive controller for volumetric display of neuroimaging studies

NASA Astrophysics Data System (ADS)

Bleiberg, Ben; Senseney, Justin; Caban, Jesus

2014-03-01

Volumetric display of medical images is an increasingly relevant method for examining an imaging acquisition as the prevalence of thin-slice imaging increases in clinical studies. Current mouse and keyboard implementations for volumetric control provide neither the sensitivity nor specificity required to manipulate a volumetric display for efficient reading in a clinical setting. Solutions to efficient volumetric manipulation provide more sensitivity by removing the binary nature of actions controlled by keyboard clicks, but specificity is lost because a single action may change display in several directions. When specificity is then further addressed by re-implementing hardware binary functions through the introduction of mode control, the result is a cumbersome interface that fails to achieve the revolutionary benefit required for adoption of a new technology. We address the specificity versus sensitivity problem of volumetric interfaces by providing adaptive positional awareness to the volumetric control device by manipulating communication between hardware driver and existing software methods for volumetric display of medical images. This creates a tethered effect for volumetric display, providing a smooth interface that improves on existing hardware approaches to volumetric scene manipulation.

New Methods of Low-Field Magnetic Resonance Imaging for Application to Traumatic Brain Injury

DTIC Science & Technology

2013-02-01

magnet based ), the development of novel high-speed parallel imaging detection systems, and work on advanced adaptive reconstruction methods ...signal many times within the acquisition time . We present here a new method for 3D OMRI based on b-SSFP at a constant field of 6.5 mT that provides up...developing injury-sensitive MRI based on the detection of free radicals associat- ed with injury using the Overhauser effect and subsequently imaging that

Automated detection of nerve fiber layer defects on retinal fundus images using fully convolutional network for early diagnosis of glaucoma

NASA Astrophysics Data System (ADS)

Watanabe, Ryusuke; Muramatsu, Chisako; Ishida, Kyoko; Sawada, Akira; Hatanaka, Yuji; Yamamoto, Tetsuya; Fujita, Hiroshi

2017-03-01

Early detection of glaucoma is important to slow down progression of the disease and to prevent total vision loss. We have been studying an automated scheme for detection of a retinal nerve fiber layer defect (NFLD), which is one of the earliest signs of glaucoma on retinal fundus images. In our previous study, we proposed a multi-step detection scheme which consists of Gabor filtering, clustering and adaptive thresholding. The problems of the previous method were that the number of false positives (FPs) was still large and that the method included too many rules. In attempt to solve these problems, we investigated the end-to-end learning system without pre-specified features. A deep convolutional neural network (DCNN) with deconvolutional layers was trained to detect NFLD regions. In this preliminary investigation, we investigated effective ways of preparing the input images and compared the detection results. The optimal result was then compared with the result obtained by the previous method. DCNN training was carried out using original images of abnormal cases, original images of both normal and abnormal cases, ellipse-based polar transformed images, and transformed half images. The result showed that use of both normal and abnormal cases increased the sensitivity as well as the number of FPs. Although NFLDs are visualized with the highest contrast in green plane, the use of color images provided higher sensitivity than the use of green image only. The free response receiver operating characteristic curve using the transformed color images, which was the best among seven different sets studied, was comparable to that of the previous method. Use of DCNN has a potential to improve the generalizability of automated detection method of NFLDs and may be useful in assisting glaucoma diagnosis on retinal fundus images.

Quantification of tumor fluorescence during intraoperative optical cancer imaging.

PubMed

Judy, Ryan P; Keating, Jane J; DeJesus, Elizabeth M; Jiang, Jack X; Okusanya, Olugbenga T; Nie, Shuming; Holt, David E; Arlauckas, Sean P; Low, Phillip S; Delikatny, E James; Singhal, Sunil

2015-11-13

Intraoperative optical cancer imaging is an emerging technology in which surgeons employ fluorophores to visualize tumors, identify tumor-positive margins and lymph nodes containing metastases. This study compares instrumentation to measure tumor fluorescence. Three imaging systems (Spectropen, Glomax, Flocam) measured and quantified fluorescent signal-to-background ratios (SBR) in vitro, murine xenografts, tissue phantoms and clinically. Evaluation criteria included the detection of small changes in fluorescence, sensitivity of signal detection at increasing depths and practicality of use. In vitro, spectroscopy was superior in detecting incremental differences in fluorescence than luminescence and digital imaging (Ln[SBR] = 6.8 ± 0.6, 2.4 ± 0.3, 2.6 ± 0.1, p = 0.0001). In fluorescent tumor cells, digital imaging measured higher SBRs than luminescence (6.1 ± 0.2 vs. 4.3 ± 0.4, p = 0.001). Spectroscopy was more sensitive than luminometry and digital imaging in identifying murine tumor fluorescence (SBR = 41.7 ± 11.5, 5.1 ± 1.8, 4.1 ± 0.9, p = 0.0001), and more sensitive than digital imaging at detecting fluorescence at increasing depths (SBR = 7.0 ± 3.4 vs. 2.4 ± 0.5, p = 0.03). Lastly, digital imaging was the most practical and least time-consuming. All methods detected incremental differences in fluorescence. Spectroscopy was the most sensitive for small changes in fluorescence. Digital imaging was the most practical considering its wide field of view, background noise filtering capability, and sensitivity to increasing depth.

Fluorescence of Picrosirius Red Multiplexed With Immunohistochemistry for the Quantitative Assessment of Collagen in Tissue Sections.

PubMed

Wegner, Kyle A; Keikhosravi, Adib; Eliceiri, Kevin W; Vezina, Chad M

2017-08-01

The low cost and simplicity of picrosirius red (PSR) staining have driven its popularity for collagen detection in tissue sections. We extended the versatility of this method by using fluorescent imaging to detect the PSR signal and applying automated quantification tools. We also developed the first PSR protocol that is fully compatible with multiplex immunostaining, making it possible to test whether collagen structure differs across immunohistochemically labeled regions of the tissue landscape. We compared our imaging method with two gold standards in collagen imaging, linear polarized light microscopy and second harmonic generation imaging, and found that it is at least as sensitive and robust to changes in sample orientation. As proof of principle, we used a genetic approach to overexpress beta catenin in a patchy subset of mouse prostate epithelial cells distinguished only by immunolabeling. We showed that collagen fiber length is significantly greater near beta catenin overexpressing cells than near control cells. Our fluorescent PSR imaging method is sensitive, reproducible, and offers a new way to guide region of interest selection for quantifying collagen in tissue sections.

Image Hashes as Templates for Verification

DOE Office of Scientific and Technical Information (OSTI.GOV)

Janik, Tadeusz; Jarman, Kenneth D.; Robinson, Sean M.

2012-07-17

Imaging systems can provide measurements that confidently assess characteristics of nuclear weapons and dismantled weapon components, and such assessment will be needed in future verification for arms control. Yet imaging is often viewed as too intrusive, raising concern about the ability to protect sensitive information. In particular, the prospect of using image-based templates for verifying the presence or absence of a warhead, or of the declared configuration of fissile material in storage, may be rejected out-of-hand as being too vulnerable to violation of information barrier (IB) principles. Development of a rigorous approach for generating and comparing reduced-information templates from images,more » and assessing the security, sensitivity, and robustness of verification using such templates, are needed to address these concerns. We discuss our efforts to develop such a rigorous approach based on a combination of image-feature extraction and encryption-utilizing hash functions to confirm proffered declarations, providing strong classified data security while maintaining high confidence for verification. The proposed work is focused on developing secure, robust, tamper-sensitive and automatic techniques that may enable the comparison of non-sensitive hashed image data outside an IB. It is rooted in research on so-called perceptual hash functions for image comparison, at the interface of signal/image processing, pattern recognition, cryptography, and information theory. Such perceptual or robust image hashing—which, strictly speaking, is not truly cryptographic hashing—has extensive application in content authentication and information retrieval, database search, and security assurance. Applying and extending the principles of perceptual hashing to imaging for arms control, we propose techniques that are sensitive to altering, forging and tampering of the imaged object yet robust and tolerant to content-preserving image distortions and noise. Ensuring that the information contained in the hashed image data (available out-of-IB) cannot be used to extract sensitive information about the imaged object is of primary concern. Thus the techniques are characterized by high unpredictability to guarantee security. We will present an assessment of the performance of our techniques with respect to security, sensitivity and robustness on the basis of a methodical and mathematically precise framework.« less

A single-pixel X-ray imager concept and its application to secure radiographic inspections

DOE PAGES

Gilbert, Andrew J.; Miller, Brian W.; Robinson, Sean M.; ...

2017-07-01

Imaging technology is generally considered too invasive for arms control inspections due to the concern that it cannot properly secure sensitive features of the inspected item. But, this same sensitive information, which could include direct information on the form and function of the items under inspection, could be used for robust arms control inspections. The single-pixel X-ray imager (SPXI) is introduced as a method to make such inspections, capturing the salient spatial information of an object in a secure manner while never forming an actual image. We built this method on the theory of compressive sensing and the single pixelmore » optical camera. The performance of the system is quantified using simulated inspections of simple objects. Measures of the robustness and security of the method are introduced and used to determine how robust and secure such an inspection would be. Particularly, it is found that an inspection with low noise (<1%) and high undersampling (>256×) exhibits high robustness and security.« less

A single-pixel X-ray imager concept and its application to secure radiographic inspections

NASA Astrophysics Data System (ADS)

Gilbert, Andrew J.; Miller, Brian W.; Robinson, Sean M.; White, Timothy A.; Pitts, William Karl; Jarman, Kenneth D.; Seifert, Allen

2017-07-01

Imaging technology is generally considered too invasive for arms control inspections due to the concern that it cannot properly secure sensitive features of the inspected item. However, this same sensitive information, which could include direct information on the form and function of the items under inspection, could be used for robust arms control inspections. The single-pixel X-ray imager (SPXI) is introduced as a method to make such inspections, capturing the salient spatial information of an object in a secure manner while never forming an actual image. The method is built on the theory of compressive sensing and the single pixel optical camera. The performance of the system is quantified using simulated inspections of simple objects. Measures of the robustness and security of the method are introduced and used to determine how robust and secure such an inspection would be. In particular, it is found that an inspection with low noise ( < 1 %) and high undersampling ( > 256 ×) exhibits high robustness and security.

Quantifying cell mono-layer cultures by video imaging.

PubMed

Miller, K S; Hook, L A

1996-04-01

A method is described in which the relative number of adherent cells in multi-well tissue-culture plates is assayed by staining the cells with Giemsa and capturing the image of the stained cells with a video camera and charged-coupled device. The resultant image is quantified using the associated video imaging software. The method is shown to be sensitive and reproducible and should be useful for studies where quantifying relative cell numbers and/or proliferation in vitro is required.

Digital imaging biomarkers feed machine learning for melanoma screening.

PubMed

Gareau, Daniel S; Correa da Rosa, Joel; Yagerman, Sarah; Carucci, John A; Gulati, Nicholas; Hueto, Ferran; DeFazio, Jennifer L; Suárez-Fariñas, Mayte; Marghoob, Ashfaq; Krueger, James G

2017-07-01

We developed an automated approach for generating quantitative image analysis metrics (imaging biomarkers) that are then analysed with a set of 13 machine learning algorithms to generate an overall risk score that is called a Q-score. These methods were applied to a set of 120 "difficult" dermoscopy images of dysplastic nevi and melanomas that were subsequently excised/classified. This approach yielded 98% sensitivity and 36% specificity for melanoma detection, approaching sensitivity/specificity of expert lesion evaluation. Importantly, we found strong spectral dependence of many imaging biomarkers in blue or red colour channels, suggesting the need to optimize spectral evaluation of pigmented lesions. © 2016 The Authors. Experimental Dermatology Published by John Wiley & Sons Ltd.

Fast and robust brain tumor segmentation using level set method with multiple image information.

PubMed

Lok, Ka Hei; Shi, Lin; Zhu, Xianlun; Wang, Defeng

2017-01-01

Brain tumor segmentation is a challenging task for its variation in intensity. The phenomenon is caused by the inhomogeneous content of tumor tissue and the choice of imaging modality. In 2010 Zhang developed the Selective Binary Gaussian Filtering Regularizing Level Set (SBGFRLS) model that combined the merits of edge-based and region-based segmentation. To improve the SBGFRLS method by modifying the singed pressure force (SPF) term with multiple image information and demonstrate effectiveness of proposed method on clinical images. In original SBGFRLS model, the contour evolution direction mainly depends on the SPF. By introducing a directional term in SPF, the metric could control the evolution direction. The SPF is altered by statistic values enclosed by the contour. This concept can be extended to jointly incorporate multiple image information. The new SPF term is expected to bring a solution for blur edge problem in brain tumor segmentation. The proposed method is validated with clinical images including pre- and post-contrast magnetic resonance images. The accuracy and robustness is compared with sensitivity, specificity, DICE similarity coefficient and Jaccard similarity index. Experimental results show improvement, in particular the increase of sensitivity at the same specificity, in segmenting all types of tumors except for the diffused tumor. The novel brain tumor segmentation method is clinical-oriented with fast, robust and accurate implementation and a minimal user interaction. The method effectively segmented homogeneously enhanced, non-enhanced, heterogeneously-enhanced, and ring-enhanced tumor under MR imaging. Though the method is limited by identifying edema and diffuse tumor, several possible solutions are suggested to turn the curve evolution into a fully functional clinical diagnosis tool.

Automatic diagnosis of imbalanced ophthalmic images using a cost-sensitive deep convolutional neural network.

PubMed

Jiang, Jiewei; Liu, Xiyang; Zhang, Kai; Long, Erping; Wang, Liming; Li, Wangting; Liu, Lin; Wang, Shuai; Zhu, Mingmin; Cui, Jiangtao; Liu, Zhenzhen; Lin, Zhuoling; Li, Xiaoyan; Chen, Jingjing; Cao, Qianzhong; Li, Jing; Wu, Xiaohang; Wang, Dongni; Wang, Jinghui; Lin, Haotian

2017-11-21

Ocular images play an essential role in ophthalmological diagnoses. Having an imbalanced dataset is an inevitable issue in automated ocular diseases diagnosis; the scarcity of positive samples always tends to result in the misdiagnosis of severe patients during the classification task. Exploring an effective computer-aided diagnostic method to deal with imbalanced ophthalmological dataset is crucial. In this paper, we develop an effective cost-sensitive deep residual convolutional neural network (CS-ResCNN) classifier to diagnose ophthalmic diseases using retro-illumination images. First, the regions of interest (crystalline lens) are automatically identified via twice-applied Canny detection and Hough transformation. Then, the localized zones are fed into the CS-ResCNN to extract high-level features for subsequent use in automatic diagnosis. Second, the impacts of cost factors on the CS-ResCNN are further analyzed using a grid-search procedure to verify that our proposed system is robust and efficient. Qualitative analyses and quantitative experimental results demonstrate that our proposed method outperforms other conventional approaches and offers exceptional mean accuracy (92.24%), specificity (93.19%), sensitivity (89.66%) and AUC (97.11%) results. Moreover, the sensitivity of the CS-ResCNN is enhanced by over 13.6% compared to the native CNN method. Our study provides a practical strategy for addressing imbalanced ophthalmological datasets and has the potential to be applied to other medical images. The developed and deployed CS-ResCNN could serve as computer-aided diagnosis software for ophthalmologists in clinical application.

Thermographic image analysis for classification of ACL rupture disease, bone cancer, and feline hyperthyroid, with Gabor filters

NASA Astrophysics Data System (ADS)

Alvandipour, Mehrdad; Umbaugh, Scott E.; Mishra, Deependra K.; Dahal, Rohini; Lama, Norsang; Marino, Dominic J.; Sackman, Joseph

2017-05-01

Thermography and pattern classification techniques are used to classify three different pathologies in veterinary images. Thermographic images of both normal and diseased animals were provided by the Long Island Veterinary Specialists (LIVS). The three pathologies are ACL rupture disease, bone cancer, and feline hyperthyroid. The diagnosis of these diseases usually involves radiology and laboratory tests while the method that we propose uses thermographic images and image analysis techniques and is intended for use as a prescreening tool. Images in each category of pathologies are first filtered by Gabor filters and then various features are extracted and used for classification into normal and abnormal classes. Gabor filters are linear filters that can be characterized by the two parameters wavelength λ and orientation θ. With two different wavelength and five different orientations, a total of ten different filters were studied. Different combinations of camera views, filters, feature vectors, normalization methods, and classification methods, produce different tests that were examined and the sensitivity, specificity and success rate for each test were produced. Using the Gabor features alone, sensitivity, specificity, and overall success rates of 85% for each of the pathologies was achieved.

Repeatability and comparison of clinical techniques for anterior chamber angle assessment.

PubMed

Campbell, Peter; Redmond, Tony; Agarwal, Rishi; Marshall, Lewis R; Evans, Bruce J W

2015-03-01

To assess the repeatability of gonioscopy, van Herick method and anterior segment Optical Coherence Tomography (AS-OCT) and determine the agreement between these techniques within a community optometry setting. Gonioscopy, van Herick method and AS-OCT imaging were performed by an optometrist on two occasions, 1 month apart, on 80 subjects aged over 40 years recruited from community optometry practices. Anterior segment images were captured with a spectral domain OCT (Topcon 3D OCT-2000; wavelength 840 nm) set to the Anterior Segment (AS) mode. Eyes were graded as open or occludable for each method. AS-OCT images from both visits were graded by a second optometrist masked to the gonioscopy and van Herick method results, and the visit on which the images were acquired. Cohen's kappa (κ) was used to describe the intra-observer repeatability. Likelihood ratios, sensitivity and specificity of van Herick method and AS-OCT were calculated, using gonioscopy as the reference standard. Measurements were obtained from 80 eyes of 80 subjects. In four cases, AS-OCT images were un-gradable due to difficulty in locating the scleral spur. The repeatability of gonioscopy was fair κ = 0.29, while that of the van Herick method (κ = 0.54) and AS-OCT (κ = 0.47) were somewhat better. The van Herick method showed good sensitivity (visit 1: 75%, visit 2: 69%) and high specificity (visit 1: 88%, visit 2: 96%). The sensitivity of AS-OCT was fair (visit 1: 46%, visit 2: 25%), but specificity was high (visit 1: 87%. visit 2: 89%). Intra-observer repeatability was better for van Herick method and for AS-OCT than for gonioscopy, despite the latter being considered the gold standard method. The van Herick method appeared to be more sensitive than AS-OCT when identifying eyes at risk of angle closure. A standalone anterior segment OCT with a longer wavelength laser could afford better visualisation of the angle, and might therefore be expected to enable the examiner to make more precise classifications. These instruments are not widely used by optometrists in clinical practice in the UK at present. © 2015 The Authors Ophthalmic & Physiological Optics © 2015 The College of Optometrists.

A Single-Institution Experience in Percutaneous Image-Guided Biopsy of Malignant Pleural Mesothelioma

DOE Office of Scientific and Technical Information (OSTI.GOV)

Welch, B. T., E-mail: Welch.brian@mayo.edu; Eiken, P. W.; Atwell, T. D.

PurposeMesothelioma has been considered a difficult pathologic diagnosis to achieve via image-guided core needle biopsy. The purpose of this study was to assess the diagnostic sensitivity of percutaneous image-guided biopsy for diagnosis of pleural mesothelioma.Materials and MethodsRetrospective review was performed to identify patients with a confirmed diagnosis of pleural mesothelioma and who underwent image-guided needle biopsy between January 1, 2002, and January 1, 2016. Thirty-two patients with pleural mesothelioma were identified and included for analysis in 33 image-guided biopsy procedures. Patient, procedural, and pathologic characteristics were recorded. Complications were characterized via standardized nomenclature [Common Terminology for Clinically Adverse Events (CTCAE)].ResultsPercutaneousmore » image-guided biopsy was associated with an overall sensitivity of 81%. No CTCAE clinically significant complications were observed. No image-guided procedures were complicated by pneumothorax or necessitated chest tube placement. No patients had tumor seeding of the biopsy tract.ConclusionPercutaneous image-guided biopsy can achieve high sensitivity for pathologic diagnosis of pleural mesothelioma with a low procedural complication rate, potentially obviating need for surgical biopsy.« less

Effect of image quality on calcification detection in digital mammography

PubMed Central

Warren, Lucy M.; Mackenzie, Alistair; Cooke, Julie; Given-Wilson, Rosalind M.; Wallis, Matthew G.; Chakraborty, Dev P.; Dance, David R.; Bosmans, Hilde; Young, Kenneth C.

2012-01-01

Purpose: This study aims to investigate if microcalcification detection varies significantly when mammographic images are acquired using different image qualities, including: different detectors, dose levels, and different image processing algorithms. An additional aim was to determine how the standard European method of measuring image quality using threshold gold thickness measured with a CDMAM phantom and the associated limits in current EU guidelines relate to calcification detection. Methods: One hundred and sixty two normal breast images were acquired on an amorphous selenium direct digital (DR) system. Microcalcification clusters extracted from magnified images of slices of mastectomies were electronically inserted into half of the images. The calcification clusters had a subtle appearance. All images were adjusted using a validated mathematical method to simulate the appearance of images from a computed radiography (CR) imaging system at the same dose, from both systems at half this dose, and from the DR system at quarter this dose. The original 162 images were processed with both Hologic and Agfa (Musica-2) image processing. All other image qualities were processed with Agfa (Musica-2) image processing only. Seven experienced observers marked and rated any identified suspicious regions. Free response operating characteristic (FROC) and ROC analyses were performed on the data. The lesion sensitivity at a nonlesion localization fraction (NLF) of 0.1 was also calculated. Images of the CDMAM mammographic test phantom were acquired using the automatic setting on the DR system. These images were modified to the additional image qualities used in the observer study. The images were analyzed using automated software. In order to assess the relationship between threshold gold thickness and calcification detection a power law was fitted to the data. Results: There was a significant reduction in calcification detection using CR compared with DR: the alternative FROC (AFROC) area decreased from 0.84 to 0.63 and the ROC area decreased from 0.91 to 0.79 (p < 0.0001). This corresponded to a 30% drop in lesion sensitivity at a NLF equal to 0.1. Detection was also sensitive to the dose used. There was no significant difference in detection between the two image processing algorithms used (p > 0.05). It was additionally found that lower threshold gold thickness from CDMAM analysis implied better cluster detection. The measured threshold gold thickness passed the acceptable limit set in the EU standards for all image qualities except half dose CR. However, calcification detection varied significantly between image qualities. This suggests that the current EU guidelines may need revising. Conclusions: Microcalcification detection was found to be sensitive to detector and dose used. Standard measurements of image quality were a good predictor of microcalcification cluster detection. PMID:22755704

High sensitivity contrast enhanced optical coherence tomography for functional in vivo imaging

NASA Astrophysics Data System (ADS)

Liba, Orly; SoRelle, Elliott D.; Sen, Debasish; de la Zerda, Adam

2017-02-01

In this study, we developed and applied highly-scattering large gold nanorods (LGNRs) and custom spectral detection algorithms for high sensitivity contrast-enhanced optical coherence tomography (OCT). We were able to detect LGNRs at a concentration as low as 50 pM in blood. We used this approach for noninvasive 3D imaging of blood vessels deep in solid tumors in living mice. Additionally, we demonstrated multiplexed imaging of spectrally-distinct LGNRs that enabled observations of functional drainage in lymphatic networks. This method, which we call MOZART, provides a platform for molecular imaging and characterization of tissue noninvasively at cellular resolution.

Combining inkjet printing and sol-gel chemistry for making pH-sensitive surfaces.

PubMed

Orsi, Gianni; De Maria, Carmelo; Montemurro, Francesca; Chauhan, Veeren M; Aylott, Jonathan W; Vozzi, Giovanni

2015-01-01

Today biomedical sciences are experiencing the importance of imaging biological parameters with luminescence methods. Studying 2D pH distribution with those methods allows building knowledge about complex cellular processes. Immobilizing pH sensitive nanoparticles inside hydrogel matrixes, in order to guarantee a proper SNR, could easily make stable and biocompatible 2D sensors. Inkjet printing is also well known as tool for printing images onto porous surfaces. Recently it has been used as a free-form fabrication method for building three-dimensional parts, and now is being explored as a way of printing electrical and optical devices. Inkjet printing was used either as a rapid prototyping method for custom biosensors. Sol-gel method is naturally bound with inkjet, because the picoliter-sized ink droplets evaporate quickly, thus allowing quick sol-gel transitions on the printed surface. In this work will be shown how to merge those technologies, in order to make a nanoparticles doped printable hydrogel, which could be used for making 2D/3D smart scaffolds able to monitor cell activities. An automated image analysis system was developed in order to quickly have the pH measurements from pH nanosensors fluorescence images.

Robust water fat separated dual-echo MRI by phase-sensitive reconstruction.

PubMed

Romu, Thobias; Dahlström, Nils; Leinhard, Olof Dahlqvist; Borga, Magnus

2017-09-01

The purpose of this work was to develop and evaluate a robust water-fat separation method for T1-weighted symmetric two-point Dixon data. A method for water-fat separation by phase unwrapping of the opposite-phase images by phase-sensitive reconstruction (PSR) is introduced. PSR consists of three steps; (1), identification of clusters of tissue voxels; (2), unwrapping of the phase in each cluster by solving Poisson's equation; and (3), finding the correct sign of each unwrapped opposite-phase cluster, so that the water-fat images are assigned the correct identities. Robustness was evaluated by counting the number of water-fat swap artifacts in a total of 733 image volumes. The method was also compared to commercial software. In the water-fat separated image volumes, the PSR method failed to unwrap the phase of one cluster and misclassified 10. One swap was observed in areas affected by motion and was constricted to the affected area. Twenty swaps were observed surrounding susceptibility artifacts, none of which spread outside the artifact affected regions. The PSR method had fewer swaps when compared to commercial software. The PSR method can robustly produce water-fat separated whole-body images based on symmetric two-echo spoiled gradient echo images, under both ideal conditions and in the presence of common artifacts. Magn Reson Med 78:1208-1216, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

Acoustic, elastic and poroelastic simulations of CO2 sequestration crosswell monitoring based on spectral-element and adjoint methods

NASA Astrophysics Data System (ADS)

Morency, Christina; Luo, Yang; Tromp, Jeroen

2011-05-01

The key issues in CO2 sequestration involve accurate monitoring, from the injection stage to the prediction and verification of CO2 movement over time, for environmental considerations. '4-D seismics' is a natural non-intrusive monitoring technique which involves 3-D time-lapse seismic surveys. Successful monitoring of CO2 movement requires a proper description of the physical properties of a porous reservoir. We investigate the importance of poroelasticity by contrasting poroelastic simulations with elastic and acoustic simulations. Discrepancies highlight a poroelastic signature that cannot be captured using an elastic or acoustic theory and that may play a role in accurately imaging and quantifying injected CO2. We focus on time-lapse crosswell imaging and model updating based on Fréchet derivatives, or finite-frequency sensitivity kernels, which define the sensitivity of an observable to the model parameters. We compare results of time-lapse migration imaging using acoustic, elastic (with and without the use of Gassmann's formulae) and poroelastic models. Our approach highlights the influence of using different physical theories for interpreting seismic data, and, more importantly, for extracting the CO2 signature from seismic waveforms. We further investigate the differences between imaging with the direct compressional wave, as is commonly done, versus using both direct compressional (P) and shear (S) waves. We conclude that, unlike direct P-wave traveltimes, a combination of direct P- and S-wave traveltimes constrains most parameters. Adding P- and S-wave amplitude information does not drastically improve parameter sensitivity, but it does improve spatial resolution of the injected CO2 zone. The main advantage of using a poroelastic theory lies in direct sensitivity to fluid properties. Simulations are performed using a spectral-element method, and finite-frequency sensitivity kernels are calculated using an adjoint method.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Warren, Lucy M.; Mackenzie, Alistair; Cooke, Julie

Purpose: This study aims to investigate if microcalcification detection varies significantly when mammographic images are acquired using different image qualities, including: different detectors, dose levels, and different image processing algorithms. An additional aim was to determine how the standard European method of measuring image quality using threshold gold thickness measured with a CDMAM phantom and the associated limits in current EU guidelines relate to calcification detection. Methods: One hundred and sixty two normal breast images were acquired on an amorphous selenium direct digital (DR) system. Microcalcification clusters extracted from magnified images of slices of mastectomies were electronically inserted into halfmore » of the images. The calcification clusters had a subtle appearance. All images were adjusted using a validated mathematical method to simulate the appearance of images from a computed radiography (CR) imaging system at the same dose, from both systems at half this dose, and from the DR system at quarter this dose. The original 162 images were processed with both Hologic and Agfa (Musica-2) image processing. All other image qualities were processed with Agfa (Musica-2) image processing only. Seven experienced observers marked and rated any identified suspicious regions. Free response operating characteristic (FROC) and ROC analyses were performed on the data. The lesion sensitivity at a nonlesion localization fraction (NLF) of 0.1 was also calculated. Images of the CDMAM mammographic test phantom were acquired using the automatic setting on the DR system. These images were modified to the additional image qualities used in the observer study. The images were analyzed using automated software. In order to assess the relationship between threshold gold thickness and calcification detection a power law was fitted to the data. Results: There was a significant reduction in calcification detection using CR compared with DR: the alternative FROC (AFROC) area decreased from 0.84 to 0.63 and the ROC area decreased from 0.91 to 0.79 (p < 0.0001). This corresponded to a 30% drop in lesion sensitivity at a NLF equal to 0.1. Detection was also sensitive to the dose used. There was no significant difference in detection between the two image processing algorithms used (p > 0.05). It was additionally found that lower threshold gold thickness from CDMAM analysis implied better cluster detection. The measured threshold gold thickness passed the acceptable limit set in the EU standards for all image qualities except half dose CR. However, calcification detection varied significantly between image qualities. This suggests that the current EU guidelines may need revising. Conclusions: Microcalcification detection was found to be sensitive to detector and dose used. Standard measurements of image quality were a good predictor of microcalcification cluster detection.« less

Digital double random amplitude image encryption method based on the symmetry property of the parametric discrete Fourier transform

NASA Astrophysics Data System (ADS)

Bekkouche, Toufik; Bouguezel, Saad

2018-03-01

We propose a real-to-real image encryption method. It is a double random amplitude encryption method based on the parametric discrete Fourier transform coupled with chaotic maps to perform the scrambling. The main idea behind this method is the introduction of a complex-to-real conversion by exploiting the inherent symmetry property of the transform in the case of real-valued sequences. This conversion allows the encrypted image to be real-valued instead of being a complex-valued image as in all existing double random phase encryption methods. The advantage is to store or transmit only one image instead of two images (real and imaginary parts). Computer simulation results and comparisons with the existing double random amplitude encryption methods are provided for peak signal-to-noise ratio, correlation coefficient, histogram analysis, and key sensitivity.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gilbert, Andrew J.; Miller, Brian W.; Robinson, Sean M.

Imaging technology is generally considered too invasive for arms control inspections due to the concern that it cannot properly secure sensitive features of the inspected item. But, this same sensitive information, which could include direct information on the form and function of the items under inspection, could be used for robust arms control inspections. The single-pixel X-ray imager (SPXI) is introduced as a method to make such inspections, capturing the salient spatial information of an object in a secure manner while never forming an actual image. We built this method on the theory of compressive sensing and the single pixelmore » optical camera. The performance of the system is quantified using simulated inspections of simple objects. Measures of the robustness and security of the method are introduced and used to determine how robust and secure such an inspection would be. Particularly, it is found that an inspection with low noise (<1%) and high undersampling (>256×) exhibits high robustness and security.« less

Photonic crystal enhanced fluorescence immunoassay on diatom biosilica.

PubMed

Squire, Kenneth; Kong, Xianming; LeDuff, Paul; Rorrer, Gregory L; Wang, Alan X

2018-05-16

Fluorescence biosensing is one of the most established biosensing methods, particularly fluorescence spectroscopy and microscopy. These are two highly sensitive techniques but require high grade electronics and optics to achieve the desired sensitivity. Efforts have been made to implement these methods using consumer grade electronics and simple optical setups for applications such as point-of-care diagnostics, but the sensitivity inherently suffers. Sensing substrates, capable of enhancing fluorescence are thus needed to achieve high sensitivity for such applications. In this paper, we demonstrate a photonic crystal-enhanced fluorescence immunoassay biosensor using diatom biosilica, which consists of silica frustules with sub-100 nm periodic pores. Utilizing the enhanced local optical field, the Purcell effect and increased surface area from the diatom photonic crystals, we create ultrasensitive immunoassay biosensors that can significantly enhance fluorescence spectroscopy as well as fluorescence imaging. Using standard antibody-antigen-labeled antibody immunoassay protocol, we experimentally achieved 100× and 10× better detection limit with fluorescence spectroscopy and fluorescence imaging respectively. The limit of detection of the mouse IgG goes down to 10 -16 M (14 fg/mL) and 10 -15 M (140 fg/mL) for the two respective detection modalities, virtually sensing a single mouse IgG molecule on each diatom frustule. The effectively enhanced fluorescence imaging in conjunction with the simple hot-spot counting analysis method used in this paper proves the great potential of diatom fluorescence immunoassay for point-of-care biosensing. Scanning electron microscope image of biosilica diatom frustule that enables significant enhancement of fluorescence spectroscopy and fluorescence image. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Atlas-based segmentation of brainstem regions in neuromelanin-sensitive magnetic resonance images

NASA Astrophysics Data System (ADS)

Puigvert, Marc; Castellanos, Gabriel; Uranga, Javier; Abad, Ricardo; Fernández-Seara, María. A.; Pastor, Pau; Pastor, María. A.; Muñoz-Barrutia, Arrate; Ortiz de Solórzano, Carlos

2015-03-01

We present a method for the automatic delineation of two neuromelanin rich brainstem structures -substantia nigra pars compacta (SN) and locus coeruleus (LC)- in neuromelanin sensitive magnetic resonance images of the brain. The segmentation method uses a dynamic multi-image reference atlas and a pre-registration atlas selection strategy. To create the atlas, a pool of 35 images of healthy subjects was pair-wise pre-registered and clustered in groups using an affinity propagation approach. Each group of the atlas is represented by a single exemplar image. Each new target image to be segmented is registered to the exemplars of each cluster. Then all the images of the highest performing clusters are enrolled into the final atlas, and the results of the registration with the target image are propagated using a majority voting approach. All registration processes used combined one two-stage affine and one elastic B-spline algorithm, to account for global positioning, region selection and local anatomic differences. In this paper, we present the algorithm, with emphasis in the atlas selection method and the registration scheme. We evaluate the performance of the atlas selection strategy using 35 healthy subjects and 5 Parkinson's disease patients. Then, we quantified the volume and contrast ratio of neuromelanin signal of these structures in 47 normal subjects and 40 Parkinson's disease patients to confirm that this method can detect neuromelanin-containing neurons loss in Parkinson's disease patients and could eventually be used for the early detection of SN and LC damage.

The advance of non-invasive detection methods in osteoarthritis

NASA Astrophysics Data System (ADS)

Dai, Jiao; Chen, Yanping

2011-06-01

Osteoarthritis (OA) is one of the most prevalent chronic diseases which badly affected the patients' living quality and economy. Detection and evaluation technology can provide basic information for early treatment. A variety of imaging methods in OA were reviewed, such as conventional X-ray, computed tomography (CT), ultrasound (US), magnetic resonance imaging (MRI) and near-infrared spectroscopy (NIRS). Among the existing imaging modalities, the spatial resolution of X-ray is extremely high; CT is a three-dimensional method, which has high density resolution; US as an evaluation method of knee OA discriminates lesions sensitively between normal cartilage and degenerative one; as a sensitive and nonionizing method, MRI is suitable for the detection of early OA, but the cost is too expensive for routine use; NIRS is a safe, low cost modality, and is also good at detecting early stage OA. In a word, each method has its own advantages, but NIRS is provided with broader application prospect, and it is likely to be used in clinical daily routine and become the golden standard for diagnostic detection.

a Coarse-To Model for Airplane Detection from Large Remote Sensing Images Using Saliency Modle and Deep Learning

NASA Astrophysics Data System (ADS)

Song, Z. N.; Sui, H. G.

2018-04-01

High resolution remote sensing images are bearing the important strategic information, especially finding some time-sensitive-targets quickly, like airplanes, ships, and cars. Most of time the problem firstly we face is how to rapidly judge whether a particular target is included in a large random remote sensing image, instead of detecting them on a given image. The problem of time-sensitive-targets target finding in a huge image is a great challenge: 1) Complex background leads to high loss and false alarms in tiny object detection in a large-scale images. 2) Unlike traditional image retrieval, what we need to do is not just compare the similarity of image blocks, but quickly find specific targets in a huge image. In this paper, taking the target of airplane as an example, presents an effective method for searching aircraft targets in large scale optical remote sensing images. Firstly, we used an improved visual attention model utilizes salience detection and line segment detector to quickly locate suspected regions in a large and complicated remote sensing image. Then for each region, without region proposal method, a single neural network predicts bounding boxes and class probabilities directly from full images in one evaluation is adopted to search small airplane objects. Unlike sliding window and region proposal-based techniques, we can do entire image (region) during training and test time so it implicitly encodes contextual information about classes as well as their appearance. Experimental results show the proposed method is quickly identify airplanes in large-scale images.

Planar implantable sensor for in vivo measurement of cellular oxygen metabolism in brain tissue.

PubMed

Tsytsarev, Vassiliy; Akkentli, Fatih; Pumbo, Elena; Tang, Qinggong; Chen, Yu; Erzurumlu, Reha S; Papkovsky, Dmitri B

2017-04-01

Brain imaging methods are continually improving. Imaging of the cerebral cortex is widely used in both animal experiments and charting human brain function in health and disease. Among the animal models, the rodent cerebral cortex has been widely used because of patterned neural representation of the whiskers on the snout and relative ease of activating cortical tissue with whisker stimulation. We tested a new planar solid-state oxygen sensor comprising a polymeric film with a phosphorescent oxygen-sensitive coating on the working side, to monitor dynamics of oxygen metabolism in the cerebral cortex following sensory stimulation. Sensory stimulation led to changes in oxygenation and deoxygenation processes of activated areas in the barrel cortex. We demonstrate the possibility of dynamic mapping of relative changes in oxygenation in live mouse brain tissue with such a sensor. Oxygenation-based functional magnetic resonance imaging (fMRI) is very effective method for functional brain mapping but have high costs and limited spatial resolution. Optical imaging of intrinsic signal (IOS) does not provide the required sensitivity, and voltage-sensitive dye optical imaging (VSDi) has limited applicability due to significant toxicity of the voltage-sensitive dye. Our planar solid-state oxygen sensor imaging approach circumvents these limitations, providing a simple optical contrast agent with low toxicity and rapid application. The planar solid-state oxygen sensor described here can be used as a tool in visualization and real-time analysis of sensory-evoked neural activity in vivo. Further, this approach allows visualization of local neural activity with high temporal and spatial resolution. Copyright © 2017 Elsevier B.V. All rights reserved.

Methods for Evaluating Mammography Imaging Techniques

DTIC Science & Technology

2000-06-01

independent of disease prevalence . When test outcomes are dichotomous, sensitivity and specificity measure test accuracy. Sensitivity is the...phers were not provided with the disease prevalence in the The model we use accounts for within mammographer test set. Mammographers provided one

Automatic detection of anomalies in screening mammograms

PubMed Central

2013-01-01

Background Diagnostic performance in breast screening programs may be influenced by the prior probability of disease. Since breast cancer incidence is roughly half a percent in the general population there is a large probability that the screening exam will be normal. That factor may contribute to false negatives. Screening programs typically exhibit about 83% sensitivity and 91% specificity. This investigation was undertaken to determine if a system could be developed to pre-sort screening-images into normal and suspicious bins based on their likelihood to contain disease. Wavelets were investigated as a method to parse the image data, potentially removing confounding information. The development of a classification system based on features extracted from wavelet transformed mammograms is reported. Methods In the multi-step procedure images were processed using 2D discrete wavelet transforms to create a set of maps at different size scales. Next, statistical features were computed from each map, and a subset of these features was the input for a concerted-effort set of naïve Bayesian classifiers. The classifier network was constructed to calculate the probability that the parent mammography image contained an abnormality. The abnormalities were not identified, nor were they regionalized. The algorithm was tested on two publicly available databases: the Digital Database for Screening Mammography (DDSM) and the Mammographic Images Analysis Society’s database (MIAS). These databases contain radiologist-verified images and feature common abnormalities including: spiculations, masses, geometric deformations and fibroid tissues. Results The classifier-network designs tested achieved sensitivities and specificities sufficient to be potentially useful in a clinical setting. This first series of tests identified networks with 100% sensitivity and up to 79% specificity for abnormalities. This performance significantly exceeds the mean sensitivity reported in literature for the unaided human expert. Conclusions Classifiers based on wavelet-derived features proved to be highly sensitive to a range of pathologies, as a result Type II errors were nearly eliminated. Pre-sorting the images changed the prior probability in the sorted database from 37% to 74%. PMID:24330643

A 2D MTF approach to evaluate and guide dynamic imaging developments.

PubMed

Chao, Tzu-Cheng; Chung, Hsiao-Wen; Hoge, W Scott; Madore, Bruno

2010-02-01

As the number and complexity of partially sampled dynamic imaging methods continue to increase, reliable strategies to evaluate performance may prove most useful. In the present work, an analytical framework to evaluate given reconstruction methods is presented. A perturbation algorithm allows the proposed evaluation scheme to perform robustly without requiring knowledge about the inner workings of the method being evaluated. A main output of the evaluation process consists of a two-dimensional modulation transfer function, an easy-to-interpret visual rendering of a method's ability to capture all combinations of spatial and temporal frequencies. Approaches to evaluate noise properties and artifact content at all spatial and temporal frequencies are also proposed. One fully sampled phantom and three fully sampled cardiac cine datasets were subsampled (R = 4 and 8) and reconstructed with the different methods tested here. A hybrid method, which combines the main advantageous features observed in our assessments, was proposed and tested in a cardiac cine application, with acceleration factors of 3.5 and 6.3 (skip factors of 4 and 8, respectively). This approach combines features from methods such as k-t sensitivity encoding, unaliasing by Fourier encoding the overlaps in the temporal dimension-sensitivity encoding, generalized autocalibrating partially parallel acquisition, sensitivity profiles from an array of coils for encoding and reconstruction in parallel, self, hybrid referencing with unaliasing by Fourier encoding the overlaps in the temporal dimension and generalized autocalibrating partially parallel acquisition, and generalized autocalibrating partially parallel acquisition-enhanced sensitivity maps for sensitivity encoding reconstructions.

Imaging vibration of the cochlear partition of an excised guinea pig cochlea using phase-sensitive Fourier domain optical coherence tomography

NASA Astrophysics Data System (ADS)

Choudhury, Niloy; Zeng, Yaguang; Fridberger, Anders; Chen, Fangyi; Zha, Dingjun; Nuttall, Alfred L.; Wang, Ruikang K.

2011-03-01

Studying the sound stimulated vibrations of various membranes that form the complex structure of the organ of Corti in the cochlea of the inner ear is essential for understanding how the travelling sound wave of the basilar membrane couples its energy to the organ structures. In this paper we report the feasibility of using phase-sensitive Fourier domain optical coherence tomography (FD-OCT) to image the vibration of various micro-structures of the cochlea at the same time. An excised cochlea of a guinea pig was stimulated using sounds at various frequencies and vibration image was obtained. When measuring the apex area, vibration signal from different turns, which have different best response frequencies are obtained in the same image. The method has the potential to measure the response from a much wider region of the cochlea than any other currently used method. The noise floor for vibration image for the system at 200 Hz was ~0.3nm.

EIT Imaging of admittivities with a D-bar method and spatial prior: experimental results for absolute and difference imaging.

PubMed

Hamilton, S J

2017-05-22

Electrical impedance tomography (EIT) is an emerging imaging modality that uses harmless electrical measurements taken on electrodes at a body's surface to recover information about the internal electrical conductivity and or permittivity. The image reconstruction task of EIT is a highly nonlinear inverse problem that is sensitive to noise and modeling errors making the image reconstruction task challenging. D-bar methods solve the nonlinear problem directly, bypassing the need for detailed and time-intensive forward models, to provide absolute (static) as well as time-difference EIT images. Coupling the D-bar methodology with the inclusion of high confidence a priori data results in a noise-robust regularized image reconstruction method. In this work, the a priori D-bar method for complex admittivities is demonstrated effective on experimental tank data for absolute imaging for the first time. Additionally, the method is adjusted for, and tested on, time-difference imaging scenarios. The ability of the method to be used for conductivity, permittivity, absolute as well as time-difference imaging provides the user with great flexibility without a high computational cost.

A Review on Segmentation of Positron Emission Tomography Images

PubMed Central

Foster, Brent; Bagci, Ulas; Mansoor, Awais; Xu, Ziyue; Mollura, Daniel J.

2014-01-01

Positron Emission Tomography (PET), a non-invasive functional imaging method at the molecular level, images the distribution of biologically targeted radiotracers with high sensitivity. PET imaging provides detailed quantitative information about many diseases and is often used to evaluate inflammation, infection, and cancer by detecting emitted photons from a radiotracer localized to abnormal cells. In order to differentiate abnormal tissue from surrounding areas in PET images, image segmentation methods play a vital role; therefore, accurate image segmentation is often necessary for proper disease detection, diagnosis, treatment planning, and follow-ups. In this review paper, we present state-of-the-art PET image segmentation methods, as well as the recent advances in image segmentation techniques. In order to make this manuscript self-contained, we also briefly explain the fundamentals of PET imaging, the challenges of diagnostic PET image analysis, and the effects of these challenges on the segmentation results. PMID:24845019

Single grating x-ray imaging for dynamic biological systems

NASA Astrophysics Data System (ADS)

Morgan, Kaye S.; Paganin, David M.; Parsons, David W.; Donnelley, Martin; Yagi, Naoto; Uesugi, Kentaro; Suzuki, Yoshio; Takeuchi, Akihisa; Siu, Karen K. W.

2012-07-01

Biomedical studies are already benefiting from the excellent contrast offered by phase contrast x-ray imaging, but live imaging work presents several challenges. Living samples make it particularly difficult to achieve high resolution, sensitive phase contrast images, as exposures must be short and cannot be repeated. We therefore present a single-exposure, high-flux method of differential phase contrast imaging [1, 2, 3] in the context of imaging live airways for Cystic Fibrosis (CF) treatment assessment [4]. The CF study seeks to non-invasively observe the liquid lining the airways, which should increase in depth in response to effective treatments. Both high spatial resolution and sensitivity are required in order to track micron size changes in a liquid that is not easily differentiated from the tissue on which it lies. Our imaging method achieves these goals by using a single attenuation grating or grid as a reference pattern, and analyzing how the sample deforms the pattern to quantitatively retrieve the phase depth of the sample. The deformations are mapped at each pixel in the image using local cross-correlations comparing each 'sample and pattern' image with a reference 'pattern only' image taken before the sample is introduced. This produces a differential phase image, which may be integrated to give the sample phase depth.

A fast and high-sensitive dual-wavelength diffuse optical tomography system using digital lock-in photon-counting technique

NASA Astrophysics Data System (ADS)

Chen, Weiting; Yi, Xi; Zhao, Huijuan; Gao, Feng

2014-09-01

We presented a novel dual-wavelength diffuse optical imaging system which can perform 2-D or 3-D imaging fast and high-sensitively for monitoring the dynamic change of optical parameters. A newly proposed lock-in photon-counting detection method was adopted for week optical signal collection, which brought in excellent property as well as simplified geometry. Fundamental principles of the lock-in photon-counting detection were elaborately demonstrated, and the feasibility was strictly verified by the linearity experiment. Systemic performance of the prototype set up was experimentally accessed, including stray light rejection and inherent interference. Results showed that the system possessed superior anti-interference capability (under 0.58% in darkroom) compared with traditional photon-counting detection, and the crosstalk between two wavelengths was lower than 2.28%. For comprehensive assessment, 2-D phantom experiments towards relatively large dimension model (diameter of 4cm) were conducted. Different absorption targets were imaged to investigate detection sensitivity. Reconstruction image under all conditions was exciting, with a desirable SNR. Study on image quality v.s. integration time put forward a new method for accessing higher SNR with the sacrifice of measuring speed. In summary, the newly developed system showed great potential in promoting detection sensitivity as well as measuring speed. This will make substantial progress in dynamically tracking the blood concentration distribution in many clinical areas, such as small animal disease modeling, human brain activity research and thick tissues (for example, breast) diagnosis.

Sensitivity and specificity of Norwegian optometrists’ evaluation of diabetic retinopathy in single-field retinal images – a cross-sectional experimental study

PubMed Central

2013-01-01

Background In the working age group, diabetic retinopathy is a leading cause of visual impairment. Regular eye examinations and early treatment of retinopathy can prevent visual loss, so screening for diabetic retinopathy is cost-effective. Dilated retinal digital photography with the additional use of ophthalmoscopy is the most effective and robust method of diabetic retinopathy screening. The aim of this study was to estimate the sensitivity and specificity of diabetic retinopathy screening when performed by Norwegian optometrists. Methods This study employed a cross-sectional experimental design. Seventy-four optometrists working in private optometric practice were asked to screen 14 single-field retinal images for possible diabetic retinopathy. The screening was undertaken using a web-based visual identification and management of ophthalmological conditions (VIMOC) examination. The images used in the VIMOC examination were selected from a population survey and had been previously examined by two independent ophthalmologists. In order to establish a “gold standard”, images were only chosen for use in the VIMOC examination if they had elicited diagnostic agreement between the two independent ophthalmologists. To reduce the possibility of falsely high specificity occurring by chance, half the presented images were of retinas that were not affected by diabetic retinopathy. Sensitivity and specificity for diabetic retinopathy was calculated with 95% confidence intervals (CIs). Results The mean (95%CI) sensitivity for identifying eyes with any diabetic retinopathy was 67% (62% to 72%). The mean (95%CI) specificity for identifying eyes without diabetic retinopathy was 84% (80% to 89%). The mean (95%CI) sensitivity for identifying eyes with mild non-proliferative diabetic retinopathy or moderate non-proliferative diabetes was 54% (47% to 61%) and 100%, respectively. Only four optometrists (5%) met the required standard of at least 80% sensitivity and 95% specificity that has been previously set for diabetic retinopathy screening programmes. Conclusions The evaluation of retinal images for diabetic retinopathy by Norwegian optometrists does not meet the required screening standard of at least 80% sensitivity and 95% specificity. The introduction of measures to improve this situation could have implications for both formal optometric training and continuing optometric professional education. PMID:23305337

Functionalization of titanium surface with chitosan via silanation: 3D CLSM imaging of cell biocompatibility behaviour.

PubMed

Attik, G N; D'Almeida, M; Toury, B; Grosgogeat, B

2013-09-16

Biocompatibility ranks as one of the most important properties of dental materials. One of the criteria for biocompatibility is the absence of material toxicity to cells, according to the ISO 7405 and 10993 recommendations. Among numerous available methods for toxicity assessment; 3-dimensional Confocal Laser Scanning Microscopy (3D CLSM) imaging was chosen because it provides an accurate and sensitive index of living cell behavior in contact with chitosan coated tested implants. The purpose of this study was to investigate the in vitro biocompatibility of functionalized titanium with chitosan via a silanation using sensitive and innovative 3D CLSM imaging as an investigation method for cytotoxicity assessment. The biocompatibility of four samples (controls cells, TA6V, TA6V-TESBA and TA6V-TESBAChitosan) was compared in vitro after 24h of exposure. Confocal imaging was performed on cultured human gingival fibroblast (HGF1) like cells using Live/Dead® staining. Image series were obtained with a FV10i confocal biological inverted system and analyzed with FV10-ASW 3.1 Software (Olympus France). Image analysis showed no cytotoxicity in the presence of the three tested substrates after 24 h of contact. A slight decrease of cell viability was found in contact with TA6V-TESBA with and without chitosan compared to negative control cells. Our findings highlighted the use of 3D CLSM confocal imaging as a sensitive method to evaluate qualitatively and quantitatively the biocompatibility behavior of functionalized titanium with chitosan via a silanation. The biocompatibility of the new functionalized coating to HGF1 cells is as good as the reference in biomedical device implantation TA6V.

Validity of multislice computerized tomography for diagnosis of maxillofacial fractures using an independent workstation.

PubMed

Dos Santos, Denise Takehana; Costa e Silva, Adriana Paula Andrade; Vannier, Michael Walter; Cavalcanti, Marcelo Gusmão Paraiso

2004-12-01

The purpose of this study was to demonstrate the sensitivity and specificity of multislice computerized tomography (CT) for diagnosis of maxillofacial fractures following specific protocols using an independent workstation. The study population consisted of 56 patients with maxillofacial fractures who were submitted to a multislice CT. The original data were transferred to an independent workstation using volumetric imaging software to generate axial images and simultaneous multiplanar (MPR) and 3-dimensional (3D-CT) volume rendering reconstructed images. The images were then processed and interpreted by 2 examiners using the following protocols independently of each other: axial, MPR/axial, 3D-CT images, and the association of axial/MPR/3D images. The clinical/surgical findings were considered the gold standard corroborating the diagnosis of the fractures and their anatomic localization. The statistical analysis was carried out using validity and chi-squared tests. The association of axial/MPR/3D images indicated a higher sensitivity (range 95.8%) and specificity (range 99%) than the other methods regarding the analysis of all regions. CT imaging demonstrated high specificity and sensitivity for maxillofacial fractures. The association of axial/MPR/3D-CT images added important information in relationship to other CT protocols.

Diffusion-weighted and T2-weighted MR imaging for colorectal liver metastases detection in a rat model at 7 T: a comparative study using histological examination as reference.

PubMed

Wagner, Mathilde; Maggiori, Léon; Ronot, Maxime; Paradis, Valérie; Vilgrain, Valérie; Panis, Yves; Van Beers, Bernard E

2013-08-01

To compare diffusion-weighted (DW) and T2-weighted MR imaging in detecting colorectal liver metastases in a rat model, using histological examination as a reference method. Eighteen rats had four liver injections of colon cancer cells. MR examinations at 7 T included FSE-T2-weighted imaging and SE-DW MR imaging (b = 0, 20 and 150 s/mm(2)) and were analysed by two independent readers. Histological examination was performed on 0.4-mm slices. McNemar's test was used to compare the sensitivities and the Wilcoxon matched pairs test to compare the average number of false-positives per rat. One hundred and sixty-six liver metastases were identified on histological examination. The sensitivity in detecting liver metastases was significantly higher on DW MR than on T2-weighted images (99/166 (60 %) (reader 1) and 92/166 (55 %) (reader 2) versus 77/166 (46 %), P ≤ 0.001), without an increase in false-positives per rat (P = 0.773/P = 0.850). After stratification according to metastasis diameter, DW MR imaging had a significantly higher sensitivity than T2-weighted imaging only for metastases with a diameter (0.6-1.2 mm) similar to that of the spatial resolution of MR imaging in the current study. This MR study with histological correlations shows the higher sensitivity of DW relative to T2-weighted imaging at 7 T for detecting liver metastases, especially small ones. • Diffusion weighted (DW) sequences are increasingly used in magnetic resonance imaging (MRI). • DW has higher sensitivity for liver metastases than T2-weighted imaging at 7 T. • This increase in sensitivity is especially marked for small liver metastasis detection. • This higher sensitivity is confirmed in an animal model with histological correlation. • DW imaging has the potential for earlier diagnosis of small liver metastases.

Intensity correction for multichannel hyperpolarized 13C imaging of the heart.

PubMed

Dominguez-Viqueira, William; Geraghty, Benjamin J; Lau, Justin Y C; Robb, Fraser J; Chen, Albert P; Cunningham, Charles H

2016-02-01

Develop and test an analytic correction method to correct the signal intensity variation caused by the inhomogeneous reception profile of an eight-channel phased array for hyperpolarized (13) C imaging. Fiducial markers visible in anatomical images were attached to the individual coils to provide three dimensional localization of the receive hardware with respect to the image frame of reference. The coil locations and dimensions were used to numerically model the reception profile using the Biot-Savart Law. The accuracy of the coil sensitivity estimation was validated with images derived from a homogenous (13) C phantom. Numerical coil sensitivity estimates were used to perform intensity correction of in vivo hyperpolarized (13) C cardiac images in pigs. In comparison to the conventional sum-of-squares reconstruction, improved signal uniformity was observed in the corrected images. The analytical intensity correction scheme was shown to improve the uniformity of multichannel image reconstruction in hyperpolarized [1-(13) C]pyruvate and (13) C-bicarbonate cardiac MRI. The method is independent of the pulse sequence used for (13) C data acquisition, simple to implement and does not require additional scan time, making it an attractive technique for multichannel hyperpolarized (13) C MRI. © 2015 Wiley Periodicals, Inc.

Computerized detection of leukocytes in microscopic leukorrhea images.

PubMed

Zhang, Jing; Zhong, Ya; Wang, Xiangzhou; Ni, Guangming; Du, Xiaohui; Liu, Juanxiu; Liu, Lin; Liu, Yong

2017-09-01

Detection of leukocytes is critical for the routine leukorrhea exam, which is widely used in gynecological examinations. An elevated vaginal leukocyte count in women with bacterial vaginosis is a strong predictor of vaginal or cervical infections. In the routine leukorrhea exam, the counting of leukocytes is primarily performed by manual techniques. However, the viewing and counting of leukocytes from multiple high-power viewing fields on a glass slide under a microscope leads to subjectivity, low efficiency, and low accuracy. To date, many biological cells in stool, blood, and breast cancer have been studied to realize computerized detection; however, the detection of leukocytes in microscopic leukorrhea images has not been studied. Thus, there is an increasing need for computerized detection of leukocytes. There are two key processes in the computerized detection of leukocytes in digital image processing. One is segmentation; the other is intelligent classification. In this paper, we propose a combined ensemble to detect leukocytes in the microscopic leukorrhea image. After image segmentation and selecting likely leukocyte subimages, we obtain the leukocyte candidates. Then, for intelligent classification, we adopt two methods: feature extraction and classification by a support vector machine (SVM); applying a modified convolutional neural network (CNN) to the larger subimages. If different methods classify a candidate in the same category, the process is finished. If not, the outputs of the methods are provided to a classifier to further classify the candidate. After acquiring leukocyte candidates, we attempted three methods to perform classification. The first approach using features and SVM achieved 88% sensitivity, 97% specificity, and 92.5% accuracy. The second method using CNN achieved 95% sensitivity, 84% specificity, and 89.5% accuracy. Then, in the combination approach, we achieved 92% sensitivity, 95% specificity, and 93.5% accuracy. Finally, the images with marked and counted leukocytes were obtained. A novel computerized detection system was developed for automated detection of leukocytes in microscopic images. Different methods resulted in comparable overall qualities by enabling computerized detection of leukocytes. The proposed approach further improved the performance. This preliminary study proves the feasibility of computerized detection of leukocytes in clinical use. © 2017 American Association of Physicists in Medicine.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Juffmann, Thomas; Koppell, Stewart A.; Klopfer, Brannon B.

Feynman once asked physicists to build better electron microscopes to be able to watch biology at work. While electron microscopes can now provide atomic resolution, electron beam induced specimen damage precludes high resolution imaging of sensitive materials, such as single proteins or polymers. Here, we use simulations to show that an electron microscope based on a multi-pass measurement protocol enables imaging of single proteins, without averaging structures over multiple images. While we demonstrate the method for particular imaging targets, the approach is broadly applicable and is expected to improve resolution and sensitivity for a range of electron microscopy imaging modalities,more » including, for example, scanning and spectroscopic techniques. The approach implements a quantum mechanically optimal strategy which under idealized conditions can be considered interaction-free.« less

Improving mass candidate detection in mammograms via feature maxima propagation and local feature selection.

PubMed

Melendez, Jaime; Sánchez, Clara I; van Ginneken, Bram; Karssemeijer, Nico

2014-08-01

Mass candidate detection is a crucial component of multistep computer-aided detection (CAD) systems. It is usually performed by combining several local features by means of a classifier. When these features are processed on a per-image-location basis (e.g., for each pixel), mismatching problems may arise while constructing feature vectors for classification, which is especially true when the behavior expected from the evaluated features is a peaked response due to the presence of a mass. In this study, two of these problems, consisting of maxima misalignment and differences of maxima spread, are identified and two solutions are proposed. The first proposed method, feature maxima propagation, reproduces feature maxima through their neighboring locations. The second method, local feature selection, combines different subsets of features for different feature vectors associated with image locations. Both methods are applied independently and together. The proposed methods are included in a mammogram-based CAD system intended for mass detection in screening. Experiments are carried out with a database of 382 digital cases. Sensitivity is assessed at two sets of operating points. The first one is the interval of 3.5-15 false positives per image (FPs/image), which is typical for mass candidate detection. The second one is 1 FP/image, which allows to estimate the quality of the mass candidate detector's output for use in subsequent steps of the CAD system. The best results are obtained when the proposed methods are applied together. In that case, the mean sensitivity in the interval of 3.5-15 FPs/image significantly increases from 0.926 to 0.958 (p < 0.0002). At the lower rate of 1 FP/image, the mean sensitivity improves from 0.628 to 0.734 (p < 0.0002). Given the improved detection performance, the authors believe that the strategies proposed in this paper can render mass candidate detection approaches based on image location classification more robust to feature discrepancies and prove advantageous not only at the candidate detection level, but also at subsequent steps of a CAD system.

Automated fine structure image analysis method for discrimination of diabetic retinopathy stage using conjunctival microvasculature images

PubMed Central

Khansari, Maziyar M; O’Neill, William; Penn, Richard; Chau, Felix; Blair, Norman P; Shahidi, Mahnaz

2016-01-01

The conjunctiva is a densely vascularized mucus membrane covering the sclera of the eye with a unique advantage of accessibility for direct visualization and non-invasive imaging. The purpose of this study is to apply an automated quantitative method for discrimination of different stages of diabetic retinopathy (DR) using conjunctival microvasculature images. Fine structural analysis of conjunctival microvasculature images was performed by ordinary least square regression and Fisher linear discriminant analysis. Conjunctival images between groups of non-diabetic and diabetic subjects at different stages of DR were discriminated. The automated method’s discriminate rates were higher than those determined by human observers. The method allowed sensitive and rapid discrimination by assessment of conjunctival microvasculature images and can be potentially useful for DR screening and monitoring. PMID:27446692

Fluorescence background subtraction technique for hybrid fluorescence molecular tomography/x-ray computed tomography imaging of a mouse model of early stage lung cancer.

PubMed

Ale, Angelique; Ermolayev, Vladimir; Deliolanis, Nikolaos C; Ntziachristos, Vasilis

2013-05-01

The ability to visualize early stage lung cancer is important in the study of biomarkers and targeting agents that could lead to earlier diagnosis. The recent development of hybrid free-space 360-deg fluorescence molecular tomography (FMT) and x-ray computed tomography (XCT) imaging yields a superior optical imaging modality for three-dimensional small animal fluorescence imaging over stand-alone optical systems. Imaging accuracy was improved by using XCT information in the fluorescence reconstruction method. Despite this progress, the detection sensitivity of targeted fluorescence agents remains limited by nonspecific background accumulation of the fluorochrome employed, which complicates early detection of murine cancers. Therefore we examine whether x-ray CT information and bulk fluorescence detection can be combined to increase detection sensitivity. Correspondingly, we research the performance of a data-driven fluorescence background estimator employed for subtraction of background fluorescence from acquisition data. Using mice containing known fluorochromes ex vivo, we demonstrate the reduction of background signals from reconstructed images and sensitivity improvements. Finally, by applying the method to in vivo data from K-ras transgenic mice developing lung cancer, we find small tumors at an early stage compared with reconstructions performed using raw data. We conclude with the benefits of employing fluorescence subtraction in hybrid FMT-XCT for early detection studies.

Shot noise limits to sensitivity of optical interferometry

NASA Technical Reports Server (NTRS)

Prasad, Sudhakar

1992-01-01

By arguing that the limiting noise is the photoelectron shot noise, we show that the sensitivity of image synthesis by an ideal optical interferometer is independent of the details of beam-splitting and recombination. The signal-to-noise ratio of the synthesized image is proportional to the square root of the total number of photoelectrons detected by the entire array. For non-ideal interferometers, which are forced to employ a closure-phase method of indirect inference of the visibility data, essentially the same result holds for strong sources, but at weak light levels beam-splitting degrades sensitivity.

Patient-specific estimation of spatially variant image noise for a pinhole cardiac SPECT camera.

PubMed

Cuddy-Walsh, Sarah G; Wells, R Glenn

2018-05-01

New single photon emission computed tomography (SPECT) cameras using fixed pinhole collimation are increasingly popular. Pinhole collimators are known to have variable sensitivity with distance and angle from the pinhole aperture. It follows that pinhole SPECT systems will also have spatially variant sensitivity and hence spatially variant image noise. The objective of this study was to develop and validate a rapid method for analytically estimating a map of the noise magnitude in a reconstructed image using data from a single clinical acquisition. The projected voxel (PV) noise estimation method uses a modified forward projector with attenuation effects to estimate the number of photons detected from each voxel in the field-of-view. We approximate the noise for each voxel as the standard deviation of a Poisson distribution with a mean equal to the number of detected photons. An empirical formula is used to address scaling discrepancies caused by image reconstruction. Calibration coefficients are determined for the PV method by comparing it with noise measured from a nonparametrically bootstrapped set of images of a spherical uniformly filled Tc-99m water phantom. Validation studies compare PV noise estimates with bootstrapped measured noise for 31 patient images (5 min, 340 MBq, 99m Tc-tetrofosmin rest study). Bland-Altman analysis shows R 2 correlations ≥70% between the PV-estimated and -measured image noise. For the 31 patient cardiac images, the PV noise estimate has an average bias of 0.1% compared to bootstrapped noise and have a coefficient of variation (CV) ≤ 17%. The bootstrap approach to noise measurement requires 5 h of computation for each image, whereas the PV noise estimate requires only 64 s. In cardiac images, image noise due to attenuation and camera sensitivity varies on average from 4% at the apex to 9% in the basal posterior region of the heart. The standard deviation between 15 healthy patient study images (including physiological variability in the population) ranges from 6% to 16.5% over the length of the heart. The PV method provides a rapid estimate for spatially variant patient-specific image noise magnitude in a pinhole-collimated dedicated cardiac SPECT camera with a bias of -0.3% and better than 83% precision. © 2018 American Association of Physicists in Medicine.

FPGA-based multi-channel fluorescence lifetime analysis of Fourier multiplexed frequency-sweeping lifetime imaging

PubMed Central

Zhao, Ming; Li, Yu; Peng, Leilei

2014-01-01

We report a fast non-iterative lifetime data analysis method for the Fourier multiplexed frequency-sweeping confocal FLIM (Fm-FLIM) system [ Opt. Express22, 10221 ( 2014)24921725]. The new method, named R-method, allows fast multi-channel lifetime image analysis in the system’s FPGA data processing board. Experimental tests proved that the performance of the R-method is equivalent to that of single-exponential iterative fitting, and its sensitivity is well suited for time-lapse FLIM-FRET imaging of live cells, for example cyclic adenosine monophosphate (cAMP) level imaging with GFP-Epac-mCherry sensors. With the R-method and its FPGA implementation, multi-channel lifetime images can now be generated in real time on the multi-channel frequency-sweeping FLIM system, and live readout of FRET sensors can be performed during time-lapse imaging. PMID:25321778

Superpixel-based spectral classification for the detection of head and neck cancer with hyperspectral imaging

NASA Astrophysics Data System (ADS)

Chung, Hyunkoo; Lu, Guolan; Tian, Zhiqiang; Wang, Dongsheng; Chen, Zhuo Georgia; Fei, Baowei

2016-03-01

Hyperspectral imaging (HSI) is an emerging imaging modality for medical applications. HSI acquires two dimensional images at various wavelengths. The combination of both spectral and spatial information provides quantitative information for cancer detection and diagnosis. This paper proposes using superpixels, principal component analysis (PCA), and support vector machine (SVM) to distinguish regions of tumor from healthy tissue. The classification method uses 2 principal components decomposed from hyperspectral images and obtains an average sensitivity of 93% and an average specificity of 85% for 11 mice. The hyperspectral imaging technology and classification method can have various applications in cancer research and management.

Statistical identification of stimulus-activated network nodes in multi-neuron voltage-sensitive dye optical recordings.

PubMed

Fathiazar, Elham; Anemuller, Jorn; Kretzberg, Jutta

2016-08-01

Voltage-Sensitive Dye (VSD) imaging is an optical imaging method that allows measuring the graded voltage changes of multiple neurons simultaneously. In neuroscience, this method is used to reveal networks of neurons involved in certain tasks. However, the recorded relative dye fluorescence changes are usually low and signals are superimposed by noise and artifacts. Therefore, establishing a reliable method to identify which cells are activated by specific stimulus conditions is the first step to identify functional networks. In this paper, we present a statistical method to identify stimulus-activated network nodes as cells, whose activities during sensory network stimulation differ significantly from the un-stimulated control condition. This method is demonstrated based on voltage-sensitive dye recordings from up to 100 neurons in a ganglion of the medicinal leech responding to tactile skin stimulation. Without relying on any prior physiological knowledge, the network nodes identified by our statistical analysis were found to match well with published cell types involved in tactile stimulus processing and to be consistent across stimulus conditions and preparations.

Interferometric imaging of acoustical phenomena using high-speed polarization camera and 4-step parallel phase-shifting technique

NASA Astrophysics Data System (ADS)

Ishikawa, K.; Yatabe, K.; Ikeda, Y.; Oikawa, Y.; Onuma, T.; Niwa, H.; Yoshii, M.

2017-02-01

Imaging of sound aids the understanding of the acoustical phenomena such as propagation, reflection, and diffraction, which is strongly required for various acoustical applications. The imaging of sound is commonly done by using a microphone array, whereas optical methods have recently been interested due to its contactless nature. The optical measurement of sound utilizes the phase modulation of light caused by sound. Since light propagated through a sound field changes its phase as proportional to the sound pressure, optical phase measurement technique can be used for the sound measurement. Several methods including laser Doppler vibrometry and Schlieren method have been proposed for that purpose. However, the sensitivities of the methods become lower as a frequency of sound decreases. In contrast, since the sensitivities of the phase-shifting technique do not depend on the frequencies of sounds, that technique is suitable for the imaging of sounds in the low-frequency range. The principle of imaging of sound using parallel phase-shifting interferometry was reported by the authors (K. Ishikawa et al., Optics Express, 2016). The measurement system consists of a high-speed polarization camera made by Photron Ltd., and a polarization interferometer. This paper reviews the principle briefly and demonstrates the high-speed imaging of acoustical phenomena. The results suggest that the proposed system can be applied to various industrial problems in acoustical engineering.

Shearlet Features for Registration of Remotely Sensed Multitemporal Images

NASA Technical Reports Server (NTRS)

Murphy, James M.; Le Moigne, Jacqueline

2015-01-01

We investigate the role of anisotropic feature extraction methods for automatic image registration of remotely sensed multitemporal images. Building on the classical use of wavelets in image registration, we develop an algorithm based on shearlets, a mathematical generalization of wavelets that offers increased directional sensitivity. Initial experimental results on LANDSAT images are presented, which indicate superior performance of the shearlet algorithm when compared to classical wavelet algorithms.

Evaluation of a novel collimator for molecular breast tomosynthesis.

PubMed

Gilland, David R; Welch, Benjamin L; Lee, Seungjoon; Kross, Brian; Weisenberger, Andrew G

2017-11-01

This study investigated a novel gamma camera for molecular breast tomosynthesis (MBT), which is a nuclear breast imaging method that uses limited angle tomography. The camera is equipped with a variable angle, slant-hole (VASH) collimator that allows the camera to remain close to the breast throughout the acquisition. The goal of this study was to evaluate the spatial resolution and count sensitivity of this camera and to compare contrast and contrast-to-noise ratio (CNR) with conventional planar imaging using an experimental breast phantom. The VASH collimator mounts to a commercial gamma camera for breast imaging that uses a pixelated (3.2 mm), 15 × 20 cm NaI crystal. Spatial resolution was measured in planar images over a range of distances from the collimator (30-100 mm) and a range of slant angles (-25° to 25°) using 99m Tc line sources. Spatial resolution was also measured in reconstructed MBT images including in the depth dimension. The images were reconstructed from data acquired over the -25° to 25° angular range using an iterative algorithm adapted to the slant-hole geometry. Sensitivity was measured over the range of slant angles using a disk source. Measured spatial resolution and sensitivity were compared to theoretical values. Contrast and CNR were measured using a breast phantom containing spherical lesions (6.2 mm and 7.8 mm diameter) and positioned over a range of depths in the phantom. The MBT and planar methods had equal scan time, and the count density in the breast phantom data was similar to that in clinical nuclear breast imaging. The MBT method used an iterative reconstruction algorithm combined with a postreconstruction Metz filter. The measured spatial resolution in planar images agreed well with theoretical calculations over the range of distances and slant angles. The measured FWHM was 9.7 mm at 50 mm distance. In reconstructed MBT images, the spatial resolution in the depth dimension was approximately 2.2 mm greater than the other two dimensions due to the limited angle data. The measured count sensitivity agreed closely with theory over all slant angles when using a wide energy window. At 0° slant angle, measured sensitivity was 19.7 counts sec -1 μCi -1 with the open energy window and 11.2 counts sec -1 μCi -1 with a 20% wide photopeak window (126 to 154 keV). The measured CNR in the MBT images was significantly greater than in the planar images for all but the lowest CNR cases where the lesion detectability was extremely low for both MBT and planar. The 7.8 mm lesion at 37 mm depth was marginally detectable in the planar image but easily visible in the MBT image. The improved CNR with MBT was due to a large improvement in contrast, which out-weighed the increase in image noise. The spatial resolution and count sensitivity measurements with the prototype MBT system matched theoretical calculations, and the measured CNR in breast phantom images was generally greater with the MBT system compared to conventional planar imaging. These results demonstrate the potential of the proposed MBT system to improve lesion detection in nuclear breast imaging. © 2017 American Association of Physicists in Medicine.

Meta-Analyses of Diagnostic Accuracy in Imaging Journals: Analysis of Pooling Techniques and Their Effect on Summary Estimates of Diagnostic Accuracy.

PubMed

McGrath, Trevor A; McInnes, Matthew D F; Korevaar, Daniël A; Bossuyt, Patrick M M

2016-10-01

Purpose To determine whether authors of systematic reviews of diagnostic accuracy studies published in imaging journals used recommended methods for meta-analysis, and to evaluate the effect of traditional methods on summary estimates of sensitivity and specificity. Materials and Methods Medline was searched for published systematic reviews that included meta-analysis of test accuracy data limited to imaging journals published from January 2005 to May 2015. Two reviewers independently extracted study data and classified methods for meta-analysis as traditional (univariate fixed- or random-effects pooling or summary receiver operating characteristic curve) or recommended (bivariate model or hierarchic summary receiver operating characteristic curve). Use of methods was analyzed for variation with time, geographical location, subspecialty, and journal. Results from reviews in which study authors used traditional univariate pooling methods were recalculated with a bivariate model. Results Three hundred reviews met the inclusion criteria, and in 118 (39%) of those, authors used recommended meta-analysis methods. No change in the method used was observed with time (r = 0.54, P = .09); however, there was geographic (χ(2) = 15.7, P = .001), subspecialty (χ(2) = 46.7, P < .001), and journal (χ(2) = 27.6, P < .001) heterogeneity. Fifty-one univariate random-effects meta-analyses were reanalyzed with the bivariate model; the average change in the summary estimate was -1.4% (P < .001) for sensitivity and -2.5% (P < .001) for specificity. The average change in width of the confidence interval was 7.7% (P < .001) for sensitivity and 9.9% (P ≤ .001) for specificity. Conclusion Recommended methods for meta-analysis of diagnostic accuracy in imaging journals are used in a minority of reviews; this has not changed significantly with time. Traditional (univariate) methods allow overestimation of diagnostic accuracy and provide narrower confidence intervals than do recommended (bivariate) methods. (©) RSNA, 2016 Online supplemental material is available for this article.

Quantitative image analysis of immunohistochemical stains using a CMYK color model

PubMed Central

Pham, Nhu-An; Morrison, Andrew; Schwock, Joerg; Aviel-Ronen, Sarit; Iakovlev, Vladimir; Tsao, Ming-Sound; Ho, James; Hedley, David W

2007-01-01

Background Computer image analysis techniques have decreased effects of observer biases, and increased the sensitivity and the throughput of immunohistochemistry (IHC) as a tissue-based procedure for the evaluation of diseases. Methods We adapted a Cyan/Magenta/Yellow/Key (CMYK) model for automated computer image analysis to quantify IHC stains in hematoxylin counterstained histological sections. Results The spectral characteristics of the chromogens AEC, DAB and NovaRed as well as the counterstain hematoxylin were first determined using CMYK, Red/Green/Blue (RGB), normalized RGB and Hue/Saturation/Lightness (HSL) color models. The contrast of chromogen intensities on a 0–255 scale (24-bit image file) as well as compared to the hematoxylin counterstain was greatest using the Yellow channel of a CMYK color model, suggesting an improved sensitivity for IHC evaluation compared to other color models. An increase in activated STAT3 levels due to growth factor stimulation, quantified using the Yellow channel image analysis was associated with an increase detected by Western blotting. Two clinical image data sets were used to compare the Yellow channel automated method with observer-dependent methods. First, a quantification of DAB-labeled carbonic anhydrase IX hypoxia marker in 414 sections obtained from 138 biopsies of cervical carcinoma showed strong association between Yellow channel and positive color selection results. Second, a linear relationship was also demonstrated between Yellow intensity and visual scoring for NovaRed-labeled epidermal growth factor receptor in 256 non-small cell lung cancer biopsies. Conclusion The Yellow channel image analysis method based on a CMYK color model is independent of observer biases for threshold and positive color selection, applicable to different chromogens, tolerant of hematoxylin, sensitive to small changes in IHC intensity and is applicable to simple automation procedures. These characteristics are advantageous for both basic as well as clinical research in an unbiased, reproducible and high throughput evaluation of IHC intensity. PMID:17326824

Recognition of lesion correspondence on two mammographic views: a new method of false-positive reduction for computerized mass detection

NASA Astrophysics Data System (ADS)

Sahiner, Berkman; Petrick, Nicholas; Chan, Heang-Ping; Paquerault, Sophie; Helvie, Mark A.; Hadjiiski, Lubomir M.

2001-07-01

We used the correspondence of detected structures on two views of the same breast for false-positive (FP) reduction in computerized detection of mammographic masses. For each initially detected object on one view, we considered all possible pairings with objects on the other view that fell within a radial band defined by the nipple-to-object distances. We designed a 'correspondence classifier' to classify these pairs as either the same mass (a TP-TP pair) or a mismatch (a TP-FP, FP-TP or FP-FP pair). For each pair, similarity measures of morphological and texture features were derived and used as input features in the correspondence classifier. Two-view mammograms from 94 cases were used as a preliminary data set. Initial detection provided 6.3 FPs/image at 96% sensitivity. Further FP reduction in single view resulted in 1.9 FPs/image at 80% sensitivity and 1.1 FPs/image at 70% sensitivity. By combining single-view detection with the correspondence classifier, detection accuracy improved to 1.5 FPs/image at 80% sensitivity and 0.7 FPs/image at 70% sensitivity. Our preliminary results indicate that the correspondence of geometric, morphological, and textural features of a mass on two different views provides valuable additional information for reducing FPs.

Further steps toward direct magnetic resonance (MR) imaging detection of neural action currents: optimization of MR sensitivity to transient and weak currents in a conductor.

PubMed

Pell, Gaby S; Abbott, David F; Fleming, Steven W; Prichard, James W; Jackson, Graeme D

2006-05-01

The characteristics of an MRI technique that could be used for direct detection of neuronal activity are investigated. It was shown that magnitude imaging using echo planar imaging can detect transient local currents. The sensitivity of this method was thoroughly investigated. A partial k-space EPI acquisition with homodyne reconstruction was found to increase the signal change. A unique sensitivity to the position of the current pulse within the imaging sequence was demonstrated with the greatest signal change occurring when the current pulse coincides with the acquisition of the center lines of k-space. The signal change was shown to be highly sensitive to the spatial position of the current conductor relative to the voxel. Furthermore, with the use of optimization of spatial and temporal placement of the current pulse, the level of signal change obtained at this lower limit of current detectability was considerably magnified. It was possible to detect a current of 1.7 microA applied for 20 ms with an imaging time of 1.8 min. The level of sensitivity observed in our study brings us closer to that theoretically required for the detection of action currents in nerves. Copyright (c) 2006 Wiley-Liss, Inc.

Selection of optimal spectral sensitivity functions for color filter arrays.

PubMed

Parmar, Manu; Reeves, Stanley J

2010-12-01

A color image meant for human consumption can be appropriately displayed only if at least three distinct color channels are present. Typical digital cameras acquire three-color images with only one sensor. A color filter array (CFA) is placed on the sensor such that only one color is sampled at a particular spatial location. This sparsely sampled signal is then reconstructed to form a color image with information about all three colors at each location. In this paper, we show that the wavelength sensitivity functions of the CFA color filters affect both the color reproduction ability and the spatial reconstruction quality of recovered images. We present a method to select perceptually optimal color filter sensitivity functions based upon a unified spatial-chromatic sampling framework. A cost function independent of particular scenes is defined that expresses the error between a scene viewed by the human visual system and the reconstructed image that represents the scene. A constrained minimization of the cost function is used to obtain optimal values of color-filter sensitivity functions for several periodic CFAs. The sensitivity functions are shown to perform better than typical RGB and CMY color filters in terms of both the s-CIELAB ∆E error metric and a qualitative assessment.

Characterization of image heterogeneity using 2D Minkowski functionals increases the sensitivity of detection of a targeted MRI contrast agent.

PubMed

Canuto, Holly C; McLachlan, Charles; Kettunen, Mikko I; Velic, Marko; Krishnan, Anant S; Neves, Andre' A; de Backer, Maaike; Hu, D-E; Hobson, Michael P; Brindle, Kevin M

2009-05-01

A targeted Gd(3+)-based contrast agent has been developed that detects tumor cell death by binding to the phosphatidylserine (PS) exposed on the plasma membrane of dying cells. Although this agent has been used to detect tumor cell death in vivo, the differences in signal intensity between treated and untreated tumors was relatively small. As cell death is often spatially heterogeneous within tumors, we investigated whether an image analysis technique that parameterizes heterogeneity could be used to increase the sensitivity of detection of this targeted contrast agent. Two-dimensional (2D) Minkowski functionals (MFs) provided an automated and reliable method for parameterization of image heterogeneity, which does not require prior assumptions about the number of regions or features in the image, and were shown to increase the sensitivity of detection of the contrast agent as compared to simple signal intensity analysis. (c) 2009 Wiley-Liss, Inc.

An AST-ELM Method for Eliminating the Influence of Charging Phenomenon on ECT.

PubMed

Wang, Xiaoxin; Hu, Hongli; Jia, Huiqin; Tang, Kaihao

2017-12-09

Electrical capacitance tomography (ECT) is a promising imaging technology of permittivity distributions in multiphase flow. To reduce the effect of charging phenomenon on ECT measurement, an improved extreme learning machine method combined with adaptive soft-thresholding (AST-ELM) is presented and studied for image reconstruction. This method can provide a nonlinear mapping model between the capacitance values and medium distributions by using machine learning but not an electromagnetic-sensitive mechanism. Both simulation and experimental tests are carried out to validate the performance of the presented method, and reconstructed images are evaluated by relative error and correlation coefficient. The results have illustrated that the image reconstruction accuracy by the proposed AST-ELM method has greatly improved than that by the conventional methods under the condition with charging object.

An AST-ELM Method for Eliminating the Influence of Charging Phenomenon on ECT

PubMed Central

Wang, Xiaoxin; Hu, Hongli; Jia, Huiqin; Tang, Kaihao

2017-01-01

Electrical capacitance tomography (ECT) is a promising imaging technology of permittivity distributions in multiphase flow. To reduce the effect of charging phenomenon on ECT measurement, an improved extreme learning machine method combined with adaptive soft-thresholding (AST-ELM) is presented and studied for image reconstruction. This method can provide a nonlinear mapping model between the capacitance values and medium distributions by using machine learning but not an electromagnetic-sensitive mechanism. Both simulation and experimental tests are carried out to validate the performance of the presented method, and reconstructed images are evaluated by relative error and correlation coefficient. The results have illustrated that the image reconstruction accuracy by the proposed AST-ELM method has greatly improved than that by the conventional methods under the condition with charging object. PMID:29232850

Ultrasonic Imaging Technology Helps American Manufacturer of Nondestructive Evaluation Equipment Become More Competitive in the Global Market

NASA Technical Reports Server (NTRS)

1995-01-01

Sonix, Inc., of Springfield, Virginia, has implemented ultrasonic imaging methods developed at the NASA Lewis Research Center. These methods have heretofore been unavailable on commercial ultrasonic imaging systems and provide significantly more sensitive material characterization than conventional high-resolution ultrasonic c-scanning. The technology transfer is being implemented under a cooperative agreement between NASA and Sonix, and several invention disclosures have been submitted by Dr. Roth to protect Lewis interests. Sonix has developed ultrasonic imaging systems used worldwide for microelectronics, materials research, and commercial nondestructive evaluation (NDE). In 1993, Sonix won the U.S. Department of Commerce "Excellence in Exporting" award. Lewis chose to work with Sonix for two main reasons: (1) Sonix is an innovative leader in ultrasonic imaging systems, and (2) Sonix was willing to apply the improvements we developed with our in-house Sonix equipment. This symbiotic joint effort has produced mutual benefits. Sonix recognized the market potential of our new and highly sensitive methods for ultrasonic assessment of material quality. We, in turn, see the cooperative effort as an effective means for transferring our technology while helping to improve the product of a domestic firm.

Performance analysis of unsupervised optimal fuzzy clustering algorithm for MRI brain tumor segmentation.

PubMed

Blessy, S A Praylin Selva; Sulochana, C Helen

2015-01-01

Segmentation of brain tumor from Magnetic Resonance Imaging (MRI) becomes very complicated due to the structural complexities of human brain and the presence of intensity inhomogeneities. To propose a method that effectively segments brain tumor from MR images and to evaluate the performance of unsupervised optimal fuzzy clustering (UOFC) algorithm for segmentation of brain tumor from MR images. Segmentation is done by preprocessing the MR image to standardize intensity inhomogeneities followed by feature extraction, feature fusion and clustering. Different validation measures are used to evaluate the performance of the proposed method using different clustering algorithms. The proposed method using UOFC algorithm produces high sensitivity (96%) and low specificity (4%) compared to other clustering methods. Validation results clearly show that the proposed method with UOFC algorithm effectively segments brain tumor from MR images.

An analytical SMASH procedure (ASP) for sensitivity-encoded MRI.

PubMed

Lee, R F; Westgate, C R; Weiss, R G; Bottomley, P A

2000-05-01

The simultaneous acquisition of spatial harmonics (SMASH) method of imaging with detector arrays can reduce the number of phase-encoding steps, and MRI scan time several-fold. The original approach utilized numerical gradient-descent fitting with the coil sensitivity profiles to create a set of composite spatial harmonics to replace the phase-encoding steps. Here, an analytical approach for generating the harmonics is presented. A transform is derived to project the harmonics onto a set of sensitivity profiles. A sequence of Fourier, Hilbert, and inverse Fourier transform is then applied to analytically eliminate spatially dependent phase errors from the different coils while fully preserving the spatial-encoding. By combining the transform and phase correction, the original numerical image reconstruction method can be replaced by an analytical SMASH procedure (ASP). The approach also allows simulation of SMASH imaging, revealing a criterion for the ratio of the detector sensitivity profile width to the detector spacing that produces optimal harmonic generation. When detector geometry is suboptimal, a group of quasi-harmonics arises, which can be corrected and restored to pure harmonics. The simulation also reveals high-order harmonic modulation effects, and a demodulation procedure is presented that enables application of ASP to a large numbers of detectors. The method is demonstrated on a phantom and humans using a standard 4-channel phased-array MRI system. Copyright 2000 Wiley-Liss, Inc.

Development of a PET/Cerenkov-light hybrid imaging system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yamamoto, Seiichi, E-mail: s-yama@met.nagoya-u.ac.jp; Hamamura, Fuka; Kato, Katsuhiko

2014-09-15

Purpose: Cerenkov-light imaging is a new molecular imaging technology that detects visible photons from high-speed electrons using a high sensitivity optical camera. However, the merit of Cerenkov-light imaging remains unclear. If a PET/Cerenkov-light hybrid imaging system were developed, the merit of Cerenkov-light imaging would be clarified by directly comparing these two imaging modalities. Methods: The authors developed and tested a PET/Cerenkov-light hybrid imaging system that consists of a dual-head PET system, a reflection mirror located above the subject, and a high sensitivity charge coupled device (CCD) camera. The authors installed these systems inside a black box for imaging the Cerenkov-light.more » The dual-head PET system employed a 1.2 × 1.2 × 10 mm{sup 3} GSO arranged in a 33 × 33 matrix that was optically coupled to a position sensitive photomultiplier tube to form a GSO block detector. The authors arranged two GSO block detectors 10 cm apart and positioned the subject between them. The Cerenkov-light above the subject is reflected by the mirror and changes its direction to the side of the PET system and is imaged by the high sensitivity CCD camera. Results: The dual-head PET system had a spatial resolution of ∼1.2 mm FWHM and sensitivity of ∼0.31% at the center of the FOV. The Cerenkov-light imaging system's spatial resolution was ∼275μm for a {sup 22}Na point source. Using the combined PET/Cerenkov-light hybrid imaging system, the authors successfully obtained fused images from simultaneously acquired images. The image distributions are sometimes different due to the light transmission and absorption in the body of the subject in the Cerenkov-light images. In simultaneous imaging of rat, the authors found that {sup 18}F-FDG accumulation was observed mainly in the Harderian gland on the PET image, while the distribution of Cerenkov-light was observed in the eyes. Conclusions: The authors conclude that their developed PET/Cerenkov-light hybrid imaging system is useful to evaluate the merits and the limitations of Cerenkov-light imaging in molecular imaging research.« less

Prostate multimodality image registration based on B-splines and quadrature local energy.

PubMed

Mitra, Jhimli; Martí, Robert; Oliver, Arnau; Lladó, Xavier; Ghose, Soumya; Vilanova, Joan C; Meriaudeau, Fabrice

2012-05-01

Needle biopsy of the prostate is guided by Transrectal Ultrasound (TRUS) imaging. The TRUS images do not provide proper spatial localization of malignant tissues due to the poor sensitivity of TRUS to visualize early malignancy. Magnetic Resonance Imaging (MRI) has been shown to be sensitive for the detection of early stage malignancy, and therefore, a novel 2D deformable registration method that overlays pre-biopsy MRI onto TRUS images has been proposed. The registration method involves B-spline deformations with Normalized Mutual Information (NMI) as the similarity measure computed from the texture images obtained from the amplitude responses of the directional quadrature filter pairs. Registration accuracy of the proposed method is evaluated by computing the Dice Similarity coefficient (DSC) and 95% Hausdorff Distance (HD) values for 20 patients prostate mid-gland slices and Target Registration Error (TRE) for 18 patients only where homologous structures are visible in both the TRUS and transformed MR images. The proposed method and B-splines using NMI computed from intensities provide average TRE values of 2.64 ± 1.37 and 4.43 ± 2.77 mm respectively. Our method shows statistically significant improvement in TRE when compared with B-spline using NMI computed from intensities with Student's t test p = 0.02. The proposed method shows 1.18 times improvement over thin-plate splines registration with average TRE of 3.11 ± 2.18 mm. The mean DSC and the mean 95% HD values obtained with the proposed method of B-spline with NMI computed from texture are 0.943 ± 0.039 and 4.75 ± 2.40 mm respectively. The texture energy computed from the quadrature filter pairs provides better registration accuracy for multimodal images than raw intensities. Low TRE values of the proposed registration method add to the feasibility of it being used during TRUS-guided biopsy.

Optical biopsy of head and neck cancer using hyperspectral imaging and convolutional neural networks

NASA Astrophysics Data System (ADS)

Halicek, Martin; Little, James V.; Wang, Xu; Patel, Mihir; Griffith, Christopher C.; El-Deiry, Mark W.; Chen, Amy Y.; Fei, Baowei

2018-02-01

Successful outcomes of surgical cancer resection necessitate negative, cancer-free surgical margins. Currently, tissue samples are sent to pathology for diagnostic confirmation. Hyperspectral imaging (HSI) is an emerging, non-contact optical imaging technique. A reliable optical method could serve to diagnose and biopsy specimens in real-time. Using convolutional neural networks (CNNs) as a tissue classifier, we developed a method to use HSI to perform an optical biopsy of ex-vivo surgical specimens, collected from 21 patients undergoing surgical cancer resection. Training and testing on samples from different patients, the CNN can distinguish squamous cell carcinoma (SCCa) from normal aerodigestive tract tissues with an area under the curve (AUC) of 0.82, 81% accuracy, 81% sensitivity, and 80% specificity. Additionally, normal oral tissues can be sub-classified into epithelium, muscle, and glandular mucosa using a decision tree method, with an average AUC of 0.94, 90% accuracy, 93% sensitivity, and 89% specificity. After separately training on thyroid tissue, the CNN differentiates between thyroid carcinoma and normal thyroid with an AUC of 0.95, 92% accuracy, 92% sensitivity, and 92% specificity. Moreover, the CNN can discriminate medullary thyroid carcinoma from benign multi-nodular goiter (MNG) with an AUC of 0.93, 87% accuracy, 88% sensitivity, and 85% specificity. Classical-type papillary thyroid carcinoma is differentiated from benign MNG with an AUC of 0.91, 86% accuracy, 86% sensitivity, and 86% specificity. Our preliminary results demonstrate that an HSI-based optical biopsy method using CNNs can provide multi-category diagnostic information for normal head-and-neck tissue, SCCa, and thyroid carcinomas. More patient data are needed in order to fully investigate the proposed technique to establish reliability and generalizability of the work.

Stimulated Raman scattering (SRS) spectroscopic OCT (Conference Presentation)

NASA Astrophysics Data System (ADS)

Robles, Francisco E.; Zhou, Kevin C.; Fischer, Martin C.; Warren, Warren S.

2017-02-01

Optical coherence tomography (OCT) enables non-invasive, high-resolution, tomographic imaging of biological tissues by leveraging principles of low coherence interferometry; however, OCT lacks molecular specificity. Spectroscopic OCT (SOCT) overcomes this limitation by providing depth-resolved spectroscopic signatures of chromophores, but SOCT has been limited to a couple of endogenous molecules, namely hemoglobin and melanin. Stimulated Raman scattering, on the other hand, can provide highly specific molecular information of many endogenous species, but lacks the spatial and spectral multiplexing capabilities of SOCT. In this work we integrate the two methods, SRS and SOCT, to enable simultaneously multiplexed spatial and spectral imaging with sensitivity to many endogenous biochemical species that play an important role in biology and medicine. The method, termed SRS-SOCT, has the potential to achieve fast, volumetric, and highly sensitive label-free molecular imaging, which would be valuable for many applications. We demonstrate the approach by imaging excised human adipose tissue and detecting the lipids' Raman signatures in the high-wavenumber region. Details of this method along with validations and results will be presented.

The performance of magnetic resonance imaging in the detection of triangular fibrocartilage complex injury: a meta-analysis.

PubMed

Wang, Z X; Chen, S L; Wang, Q Q; Liu, B; Zhu, J; Shen, J

2015-06-01

The aim of this study was to evaluate the accuracy of magnetic resonance imaging in the detection of triangular fibrocartilage complex injury through a meta-analysis. A comprehensive literature search was conducted before 1 April 2014. All studies comparing magnetic resonance imaging results with arthroscopy or open surgery findings were reviewed, and 25 studies that satisfied the eligibility criteria were included. Data were pooled to yield pooled sensitivity and specificity, which were respectively 0.83 and 0.82. In detection of central and peripheral tears, magnetic resonance imaging had respectively a pooled sensitivity of 0.90 and 0.88 and a pooled specificity of 0.97 and 0.97. Six high-quality studies using Ringler's recommended magnetic resonance imaging parameters were selected for analysis to determine whether optimal imaging protocols yielded better results. The pooled sensitivity and specificity of these six studies were 0.92 and 0.82, respectively. The overall accuracy of magnetic resonance imaging was acceptable. For peripheral tears, the pooled data showed a relatively high accuracy. Magnetic resonance imaging with appropriate parameters are an ideal method for diagnosing different types of triangular fibrocartilage complex tears. © The Author(s) 2015.

Near-IR and CP-OCT Imaging of Suspected Occlusal Caries Lesions

PubMed Central

Simon, Jacob C.; Kang, Hobin; Staninec, Michal; Jang, Andrew T.; Chan, Kenneth H.; Darling, Cynthia L.; Lee, Robert C.; Fried, Daniel

2017-01-01

Introduction Radiographic methods have poor sensitivity for occlusal lesions and by the time the lesions are radiolucent they have typically progressed deep into the dentin. New more sensitive imaging methods are needed to detect occlusal lesions. In this study, cross-polarization optical coherence tomography (CP-OCT) and near-IR imaging were used to image questionable occlusal lesions (QOC's) that were not visible on radiographs but had been scheduled for restoration on 30 test subjects. Methods Near-IR reflectance and transillumination probes incorporating a high definition InGaAs camera and near-IR broadband light sources were used to acquire images of the lesions before restoration. The reflectance probe utilized cross-polarization and operated at wavelengths from 1500–1700-nm where there is an increase in water absorption for higher contrast. The transillumination probe was operated at 1300-nm where the transparency of enamel is highest. Tomographic images (6×6×7 mm3) of the lesions were acquired using a high-speed swept-source CP-OCT system operating at 1300-nm before and after removal of the suspected lesion. Results Near-IR reflectance imaging at 1500–1700-nm yielded significantly higher contrast (p<0.05) of the demineralization in the occlusal grooves compared with visible reflectance imaging. Stains in the occlusal grooves greatly reduced the lesion contrast in the visible range yielding negative values. Only half of the 26 lesions analyzed showed the characteristic surface demineralization and increased reflectivity below the dentinal-enamel junction (DEJ) in 3D OCT images indicative of penetration of the lesion into the dentin. Conclusion This study demonstrates that near-IR imaging methods have great potential for improving the early diagnosis of occlusal lesions. PMID:28339115

Deep convective cloud characterizations from both broadband imager and hyperspectral infrared sounder measurements

NASA Astrophysics Data System (ADS)

Ai, Yufei; Li, Jun; Shi, Wenjing; Schmit, Timothy J.; Cao, Changyong; Li, Wanbiao

2017-02-01

Deep convective storms have contributed to airplane accidents, making them a threat to aviation safety. The most common method to identify deep convective clouds (DCCs) is using the brightness temperature difference (BTD) between the atmospheric infrared (IR) window band and the water vapor (WV) absorption band. The effectiveness of the BTD method for DCC detection is highly related to the spectral resolution and signal-to-noise ratio (SNR) of the WV band. In order to understand the sensitivity of BTD to spectral resolution and SNR for DCC detection, a BTD to noise ratio method using the difference between the WV and IR window radiances is developed to assess the uncertainty of DCC identification for different instruments. We examined the case of AirAsia Flight QZ8501. The brightness temperatures (Tbs) over DCCs from this case are simulated for BTD sensitivity studies by a fast forward radiative transfer model with an opaque cloud assumption for both broadband imager (e.g., Multifunction Transport Satellite imager, MTSAT-2 imager) and hyperspectral IR sounder (e.g., Atmospheric Infrared Sounder) instruments; we also examined the relationship between the simulated Tb and the cloud top height. Results show that despite the coarser spatial resolution, BTDs measured by a hyperspectral IR sounder are much more sensitive to high cloud tops than broadband BTDs. As demonstrated in this study, a hyperspectral IR sounder can identify DCCs with better accuracy.

Accounting for hardware imperfections in EIT image reconstruction algorithms.

PubMed

Hartinger, Alzbeta E; Gagnon, Hervé; Guardo, Robert

2007-07-01

Electrical impedance tomography (EIT) is a non-invasive technique for imaging the conductivity distribution of a body section. Different types of EIT images can be reconstructed: absolute, time difference and frequency difference. Reconstruction algorithms are sensitive to many errors which translate into image artefacts. These errors generally result from incorrect modelling or inaccurate measurements. Every reconstruction algorithm incorporates a model of the physical set-up which must be as accurate as possible since any discrepancy with the actual set-up will cause image artefacts. Several methods have been proposed in the literature to improve the model realism, such as creating anatomical-shaped meshes, adding a complete electrode model and tracking changes in electrode contact impedances and positions. Absolute and frequency difference reconstruction algorithms are particularly sensitive to measurement errors and generally assume that measurements are made with an ideal EIT system. Real EIT systems have hardware imperfections that cause measurement errors. These errors translate into image artefacts since the reconstruction algorithm cannot properly discriminate genuine measurement variations produced by the medium under study from those caused by hardware imperfections. We therefore propose a method for eliminating these artefacts by integrating a model of the system hardware imperfections into the reconstruction algorithms. The effectiveness of the method has been evaluated by reconstructing absolute, time difference and frequency difference images with and without the hardware model from data acquired on a resistor mesh phantom. Results have shown that artefacts are smaller for images reconstructed with the model, especially for frequency difference imaging.

Real-time broadband terahertz spectroscopic imaging by using a high-sensitivity terahertz camera

NASA Astrophysics Data System (ADS)

Kanda, Natsuki; Konishi, Kuniaki; Nemoto, Natsuki; Midorikawa, Katsumi; Kuwata-Gonokami, Makoto

2017-02-01

Terahertz (THz) imaging has a strong potential for applications because many molecules have fingerprint spectra in this frequency region. Spectroscopic imaging in the THz region is a promising technique to fully exploit this characteristic. However, the performance of conventional techniques is restricted by the requirement of multidimensional scanning, which implies an image data acquisition time of several minutes. In this study, we propose and demonstrate a novel broadband THz spectroscopic imaging method that enables real-time image acquisition using a high-sensitivity THz camera. By exploiting the two-dimensionality of the detector, a broadband multi-channel spectrometer near 1 THz was constructed with a reflection type diffraction grating and a high-power THz source. To demonstrate the advantages of the developed technique, we performed molecule-specific imaging and high-speed acquisition of two-dimensional (2D) images. Two different sugar molecules (lactose and D-fructose) were identified with fingerprint spectra, and their distributions in one-dimensional space were obtained at a fast video rate (15 frames per second). Combined with the one-dimensional (1D) mechanical scanning of the sample, two-dimensional molecule-specific images can be obtained only in a few seconds. Our method can be applied in various important fields such as security and biomedicine.

Comparison of indium-labeled-leukocyte imaging with sequential technetium-gallium scanning in the diagnosis of low-grade musculoskeletal sepsis. A prospective study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Merkel, K.D.; Brown, M.L.; Dewanjee, M.K.

We prospectively compared sequential technetium-gallium imaging with indium-labeled-leukocyte imaging in fifty patients with suspected low-grade musculoskeletal sepsis. Adequate images and follow-up examinations were obtained for forty-two patients. The presence or absence of low-grade sepsis was confirmed by histological and bacteriological examinations of tissue specimens taken at surgery in thirty of the forty-two patients. In these thirty patients, the sensitivity of sequential Tc-Ga imaging was 48 per cent, the specificity was 86 per cent, and the accuracy was 57 per cent, whereas the sensitivity of the indium-labeled-leukocyte technique was 83 per cent, the specificity was 86 per cent, and the accuracymore » was 83 per cent. When the additional twelve patients for whom surgery was deemed unnecessary were considered, the sensitivity of sequential Tc-Ga imaging was 50 per cent, the specificity was 78 per cent, and the accuracy was 62 per cent, as compared with a sensitivity of 83 per cent, a specificity of 94 per cent, and an accuracy of 88 per cent with the indium-labeled-leukocyte method. In patients with a prosthesis the indium-labeled-leukocyte image was 94 per cent accurate, compared with 75 per cent accuracy for sequential Tc-Ga imaging. Statistical analysis of these data demonstrated that the indium-labeled-leukocyte technique was superior to sequential Tc-Ga imaging in detecting areas of low-grade musculoskeletal sepsis.« less

Hybrid statistics-simulations based method for atom-counting from ADF STEM images.

PubMed

De Wael, Annelies; De Backer, Annick; Jones, Lewys; Nellist, Peter D; Van Aert, Sandra

2017-06-01

A hybrid statistics-simulations based method for atom-counting from annular dark field scanning transmission electron microscopy (ADF STEM) images of monotype crystalline nanostructures is presented. Different atom-counting methods already exist for model-like systems. However, the increasing relevance of radiation damage in the study of nanostructures demands a method that allows atom-counting from low dose images with a low signal-to-noise ratio. Therefore, the hybrid method directly includes prior knowledge from image simulations into the existing statistics-based method for atom-counting, and accounts in this manner for possible discrepancies between actual and simulated experimental conditions. It is shown by means of simulations and experiments that this hybrid method outperforms the statistics-based method, especially for low electron doses and small nanoparticles. The analysis of a simulated low dose image of a small nanoparticle suggests that this method allows for far more reliable quantitative analysis of beam-sensitive materials. Copyright © 2017 Elsevier B.V. All rights reserved.

Molecular imaging in neuroendocrine tumors: molecular uptake mechanisms and clinical results.

PubMed

Koopmans, Klaas P; Neels, Oliver N; Kema, Ido P; Elsinga, Philip H; Links, Thera P; de Vries, Elisabeth G E; Jager, Pieter L

2009-09-01

Neuroendocrine tumors can originate almost everywhere in the body and consist of a great variety of subtypes. This paper focuses on molecular imaging methods using nuclear medicine techniques in neuroendocrine tumors, coupling molecular uptake mechanisms of radiotracers with clinical results. A non-systematic review is presented on receptor based and metabolic imaging methods. Receptor-based imaging covers the molecular backgrounds of somatostatin, vaso-intestinal peptide (VIP), bombesin and cholecystokinin (CCK) receptors and their link with nuclear imaging. Imaging methods based on specific metabolic properties include meta-iodo-benzylguanide (MIBG) and dimercapto-sulphuric acid (DMSA-V) scintigraphy as well as more modern positron emission tomography (PET)-based methods using radio-labeled analogues of amino acids, glucose, dihydroxyphenylalanine (DOPA), dopamine and tryptophan. Diagnostic sensitivities are presented for each imaging method and for each neuroendocrine tumor subtype. Finally, a Forest plot analysis of diagnostic performance is presented for each tumor type in order to provide a comprehensive overview for clinical use.

Detection of microcalcifications by characteristic magnetic susceptibility effects using MR phase image cross-correlation analysis

PubMed Central

Baheza, Richard A.; Welch, E. Brian; Gochberg, Daniel F.; Sanders, Melinda; Harvey, Sara; Gore, John C.; Yankeelov, Thomas E.

2015-01-01

Purpose: To develop and evaluate a new method for detecting calcium deposits using their characteristic magnetic susceptibility effects on magnetic resonance (MR) images at high fields and demonstrate its potential in practice for detecting breast microcalcifications. Methods: Characteristic dipole signatures of calcium deposits were detected in magnetic resonance phase images by computing the cross-correlation between the acquired data and a library of templates containing simulated phase patterns of spherical deposits. The influence of signal-to-noise ratio and various other MR parameters on the results were assessed using simulations and validated experimentally. The method was tested experimentally for detection of calcium fragments within gel phantoms and calcium-like inhomogeneities within chicken tissue at 7 T with optimized MR acquisition parameters. The method was also evaluated for detection of simulated microcalcifications, modeled from biopsy samples of malignant breast cancer, inserted in silico into breast magnetic resonance imaging (MRIs) of healthy subjects at 7 T. For both assessments of calcium fragments in phantoms and biopsy-based simulated microcalcifications in breast MRIs, receiver operator characteristic curve analyses were performed to determine the cross-correlation index cutoff, for achieving optimal sensitivity and specificity, and the area under the curve (AUC), for measuring the method’s performance. Results: The method detected calcium fragments with sizes of 0.14–0.79 mm, 1 mm calcium-like deposits, and simulated microcalcifications with sizes of 0.4–1.0 mm in images with voxel sizes between (0.2 mm)3 and (0.6 mm)3. In images acquired at 7 T with voxel sizes of (0.2 mm)3–(0.4 mm)3, calcium fragments (size 0.3–0.4 mm) were detected with a sensitivity, specificity, and AUC of 78%–90%, 51%–68%, and 0.77%–0.88%, respectively. In images acquired with a human 7 T scanner, acquisition times below 12 min, and voxel sizes of (0.4 mm)3–(0.6 mm)3, simulated microcalcifications with sizes of 0.6–1.0 mm were detected with a sensitivity, specificity, and AUC of 75%–87%, 54%–87%, and 0.76%–0.90%, respectively. However, different microcalcification shapes were indistinguishable. Conclusions: The new method is promising for detecting relatively large microcalcifications (i.e., 0.6–0.9 mm) within the breast at 7 T in reasonable times. Detection of smaller deposits at high field may be possible with higher spatial resolution, but such images require relatively long scan times. Although mammography can detect and distinguish the shape of smaller microcalcifications with superior sensitivity and specificity, this alternative method does not expose tissue to ionizing radiation, is not affected by breast density, and can be combined with other MRI methods (e.g., dynamic contrast-enhanced MRI and diffusion weighted MRI), to potentially improve diagnostic performance. PMID:25735297

Detection of microcalcifications by characteristic magnetic susceptibility effects using MR phase image cross-correlation analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Baheza, Richard A.; Welch, E. Brian; Gochberg, Daniel F.

Purpose: To develop and evaluate a new method for detecting calcium deposits using their characteristic magnetic susceptibility effects on magnetic resonance (MR) images at high fields and demonstrate its potential in practice for detecting breast microcalcifications. Methods: Characteristic dipole signatures of calcium deposits were detected in magnetic resonance phase images by computing the cross-correlation between the acquired data and a library of templates containing simulated phase patterns of spherical deposits. The influence of signal-to-noise ratio and various other MR parameters on the results were assessed using simulations and validated experimentally. The method was tested experimentally for detection of calcium fragmentsmore » within gel phantoms and calcium-like inhomogeneities within chicken tissue at 7 T with optimized MR acquisition parameters. The method was also evaluated for detection of simulated microcalcifications, modeled from biopsy samples of malignant breast cancer, inserted in silico into breast magnetic resonance imaging (MRIs) of healthy subjects at 7 T. For both assessments of calcium fragments in phantoms and biopsy-based simulated microcalcifications in breast MRIs, receiver operator characteristic curve analyses were performed to determine the cross-correlation index cutoff, for achieving optimal sensitivity and specificity, and the area under the curve (AUC), for measuring the method’s performance. Results: The method detected calcium fragments with sizes of 0.14–0.79 mm, 1 mm calcium-like deposits, and simulated microcalcifications with sizes of 0.4–1.0 mm in images with voxel sizes between (0.2 mm){sup 3} and (0.6 mm){sup 3}. In images acquired at 7 T with voxel sizes of (0.2 mm){sup 3}–(0.4 mm){sup 3}, calcium fragments (size 0.3–0.4 mm) were detected with a sensitivity, specificity, and AUC of 78%–90%, 51%–68%, and 0.77%–0.88%, respectively. In images acquired with a human 7 T scanner, acquisition times below 12 min, and voxel sizes of (0.4 mm){sup 3}–(0.6 mm){sup 3}, simulated microcalcifications with sizes of 0.6–1.0 mm were detected with a sensitivity, specificity, and AUC of 75%–87%, 54%–87%, and 0.76%–0.90%, respectively. However, different microcalcification shapes were indistinguishable. Conclusions: The new method is promising for detecting relatively large microcalcifications (i.e., 0.6–0.9 mm) within the breast at 7 T in reasonable times. Detection of smaller deposits at high field may be possible with higher spatial resolution, but such images require relatively long scan times. Although mammography can detect and distinguish the shape of smaller microcalcifications with superior sensitivity and specificity, this alternative method does not expose tissue to ionizing radiation, is not affected by breast density, and can be combined with other MRI methods (e.g., dynamic contrast-enhanced MRI and diffusion weighted MRI), to potentially improve diagnostic performance.« less

Spatial recurrence analysis: A sensitive and fast detection tool in digital mammography

DOE Office of Scientific and Technical Information (OSTI.GOV)

Prado, T. L.; Galuzio, P. P.; Lopes, S. R.

Efficient diagnostics of breast cancer requires fast digital mammographic image processing. Many breast lesions, both benign and malignant, are barely visible to the untrained eye and requires accurate and reliable methods of image processing. We propose a new method of digital mammographic image analysis that meets both needs. It uses the concept of spatial recurrence as the basis of a spatial recurrence quantification analysis, which is the spatial extension of the well-known time recurrence analysis. The recurrence-based quantifiers are able to evidence breast lesions in a way as good as the best standard image processing methods available, but with amore » better control over the spurious fragments in the image.« less

Polarization properties of amyloid-beta plaques in Alzheimer's disease (Conference Presentation)

NASA Astrophysics Data System (ADS)

Baumann, Bernhard; Wöhrer, Adelheid; Ricken, Gerda; Pircher, Michael; Kovacs, Gabor G.; Hitzenberger, Christoph K.

2016-03-01

In histopathological practice, birefringence is used for the identification of amyloidosis in numerous tissues. Amyloid birefringence is caused by the parallel arrangement of fibrous protein aggregates. Since neurodegenerative processes in Alzheimer's disease (AD) are also linked to the formation of amyloid-beta (Aβ) plaques, optical methods sensitive to birefringence may act as non-invasive tools for Aβ identification. At last year's Photonics West, we demonstrated polarization-sensitive optical coherence tomography (PS-OCT) imaging of ex vivo cerebral tissue of advanced stage AD patients. PS-OCT provides volumetric, structural imaging based on both backscatter contrast and tissue polarization properties. In this presentation, we report on polarization-sensitive neuroimaging along with numerical simulations of three-dimensional Aβ plaques. High speed PS-OCT imaging was performed using a spectral domain approach based on polarization maintaining fiber optics. The sample beam was interfaced to a confocal scanning microscope arrangement. Formalin-fixed tissue samples as well as thin histological sections were imaged. For comparison to the PS-OCT results, ray propagation through plaques was modeled using Jones analysis and various illumination geometries and plaque sizes. Characteristic polarization patterns were found. The results of this study may not only help to understand PS-OCT imaging of neuritic Aβ plaques but may also have implications for polarization-sensitive imaging of other fibrillary structures.

Computer-aided Classification of Mammographic Masses Using Visually Sensitive Image Features

PubMed Central

Wang, Yunzhi; Aghaei, Faranak; Zarafshani, Ali; Qiu, Yuchen; Qian, Wei; Zheng, Bin

2017-01-01

Purpose To develop a new computer-aided diagnosis (CAD) scheme that computes visually sensitive image features routinely used by radiologists to develop a machine learning classifier and distinguish between the malignant and benign breast masses detected from digital mammograms. Methods An image dataset including 301 breast masses was retrospectively selected. From each segmented mass region, we computed image features that mimic five categories of visually sensitive features routinely used by radiologists in reading mammograms. We then selected five optimal features in the five feature categories and applied logistic regression models for classification. A new CAD interface was also designed to show lesion segmentation, computed feature values and classification score. Results Areas under ROC curves (AUC) were 0.786±0.026 and 0.758±0.027 when to classify mass regions depicting on two view images, respectively. By fusing classification scores computed from two regions, AUC increased to 0.806±0.025. Conclusion This study demonstrated a new approach to develop CAD scheme based on 5 visually sensitive image features. Combining with a “visual aid” interface, CAD results may be much more easily explainable to the observers and increase their confidence to consider CAD generated classification results than using other conventional CAD approaches, which involve many complicated and visually insensitive texture features. PMID:27911353

Quantification of tumor fluorescence during intraoperative optical cancer imaging

PubMed Central

Judy, Ryan P.; Keating, Jane J.; DeJesus, Elizabeth M.; Jiang, Jack X.; Okusanya, Olugbenga T.; Nie, Shuming; Holt, David E.; Arlauckas, Sean P.; Low, Phillip S.; Delikatny, E. James; Singhal, Sunil

2015-01-01

Intraoperative optical cancer imaging is an emerging technology in which surgeons employ fluorophores to visualize tumors, identify tumor-positive margins and lymph nodes containing metastases. This study compares instrumentation to measure tumor fluorescence. Three imaging systems (Spectropen, Glomax, Flocam) measured and quantified fluorescent signal-to-background ratios (SBR) in vitro, murine xenografts, tissue phantoms and clinically. Evaluation criteria included the detection of small changes in fluorescence, sensitivity of signal detection at increasing depths and practicality of use. In vitro, spectroscopy was superior in detecting incremental differences in fluorescence than luminescence and digital imaging (Ln[SBR] = 6.8 ± 0.6, 2.4 ± 0.3, 2.6 ± 0.1, p = 0.0001). In fluorescent tumor cells, digital imaging measured higher SBRs than luminescence (6.1 ± 0.2 vs. 4.3 ± 0.4, p = 0.001). Spectroscopy was more sensitive than luminometry and digital imaging in identifying murine tumor fluorescence (SBR = 41.7 ± 11.5, 5.1 ± 1.8, 4.1 ± 0.9, p = 0.0001), and more sensitive than digital imaging at detecting fluorescence at increasing depths (SBR = 7.0 ± 3.4 vs. 2.4 ± 0.5, p = 0.03). Lastly, digital imaging was the most practical and least time-consuming. All methods detected incremental differences in fluorescence. Spectroscopy was the most sensitive for small changes in fluorescence. Digital imaging was the most practical considering its wide field of view, background noise filtering capability, and sensitivity to increasing depth. PMID:26563091

Retrospective and comparative analysis of (99m)Tc-Sestamibi breast specific gamma imaging versus mammography, ultrasound, and magnetic resonance imaging for the detection of breast cancer in Chinese women.

PubMed

Yu, Xiuyan; Hu, Guoming; Zhang, Zhigang; Qiu, Fuming; Shao, Xuan; Wang, Xiaochen; Zhan, Hongwei; Chen, Yiding; Deng, Yongchuan; Huang, Jian

2016-07-11

Diagnosing breast cancer during the early stage may be helpful for decreasing cancer-related mortality. In Western developed countries, mammographies have been the gold standard for breast cancer detection. However, Chinese women usually have denser and smaller-sized breasts compared to Caucasian women, which decreases the diagnostic accuracy of mammography. However, breast specific gamma imaging, a type of molecular functional breast imaging, has been used for the accurate diagnosis of breast cancer and is not influenced by breast density. Our objective was to analyze the breast specific gamma imaging (BSGI) diagnostic value for Chinese women. During a 2-year period, 357 women were diagnosed and treated at our oncology department and received BSGI in addition to mammography (MMG), ultrasound (US) and magnetic resonance imaging (MRI) for diagnostic assessment. We investigated the sensitivity and specificity of each method of detection and compared the biological profiles of the four imaging methods. A total of 357 women received a final surgical pathology diagnosis, with 168 malignant diseases (58.5 %) and 119 benign diseases (41.5 %). Of these, 166 underwent the four imaging tests preoperatively. The sensitivity of BSGI was 80.35 and 82.14 % by US, 75.6 % by MMG, and 94.06 % by MRI. Furthermore, the breast cancer diagnosis specificity of BSGI was high (83.19 % vs. 77.31 % vs. 66.39 % vs. 67.69 %, respectively). The BSGI diagnostic sensitivity for mammographic breast density in women was superior to mammography and more sensitive for non-luminal A subtypes (luminal A vs. non-luminal A, 68.63 % vs. 88.30 %). BSGI may help improve the ability to diagnose early stage breast cancer for Chinese women, particularly for ductal carcinoma in situ (DCIS), mammographic breast density and non-luminal A breast cancer.

Multi-pass transmission electron microscopy

DOE PAGES

Juffmann, Thomas; Koppell, Stewart A.; Klopfer, Brannon B.; ...

2017-05-10

Feynman once asked physicists to build better electron microscopes to be able to watch biology at work. While electron microscopes can now provide atomic resolution, electron beam induced specimen damage precludes high resolution imaging of sensitive materials, such as single proteins or polymers. Here, we use simulations to show that an electron microscope based on a multi-pass measurement protocol enables imaging of single proteins, without averaging structures over multiple images. While we demonstrate the method for particular imaging targets, the approach is broadly applicable and is expected to improve resolution and sensitivity for a range of electron microscopy imaging modalities,more » including, for example, scanning and spectroscopic techniques. The approach implements a quantum mechanically optimal strategy which under idealized conditions can be considered interaction-free.« less

Two-dimensional phase unwrapping using robust derivative estimation and adaptive integration.

PubMed

Strand, Jarle; Taxt, Torfinn

2002-01-01

The adaptive integration (ADI) method for two-dimensional (2-D) phase unwrapping is presented. The method uses an algorithm for noise robust estimation of partial derivatives, followed by a noise robust adaptive integration process. The ADI method can easily unwrap phase images with moderate noise levels, and the resulting images are congruent modulo 2pi with the observed, wrapped, input images. In a quantitative evaluation, both the ADI and the BLS methods (Strand et al.) were better than the least-squares methods of Ghiglia and Romero (GR), and of Marroquin and Rivera (MRM). In a qualitative evaluation, the ADI, the BLS, and a conjugate gradient version of the MRM method (MRMCG), were all compared using a synthetic image with shear, using 115 magnetic resonance images, and using 22 fiber-optic interferometry images. For the synthetic image and the interferometry images, the ADI method gave consistently visually better results than the other methods. For the MR images, the MRMCG method was best, and the ADI method second best. The ADI method was less sensitive to the mask definition and the block size than the BLS method, and successfully unwrapped images with shears that were not marked in the masks. The computational requirements of the ADI method for images of nonrectangular objects were comparable to only two iterations of many least-squares-based methods (e.g., GR). We believe the ADI method provides a powerful addition to the ensemble of tools available for 2-D phase unwrapping.

Time-lapse imaging assay using the BioStation CT: a sensitive drug-screening method for three-dimensional cell culture.

PubMed

Sakamoto, Ruriko; Rahman, M Mamunur; Shimomura, Manami; Itoh, Manabu; Nakatsura, Tetsuya

2015-06-01

Three-dimensional (3D) cell culture is beneficial for physiological studies of tumor cells, due to its potential to deliver a high quantity of cell culture information that is representative of the cancer microenvironment and predictive of drug responses in vivo. Currently, gel-associated or matrix-associated 3D cell culture is comprised of intricate procedures that often result in experimental complexity. Therefore, we developed an innovative anti-cancer drug sensitivity screening technique for 3D cell culture on NanoCulture Plates (NCP) by employing the imaging device BioStation CT. Here, we showed that the human breast cancer cell lines BT474 and T47D form multicellular spheroids on NCP plates and compared their sensitivity to the anti-cancer drugs trastuzumab and paclitaxel using the BioStation CT. The anticancer drugs reduced spheroid migration velocity and suppressed spheroid fusion. In addition, primary cells derived from the human breast cancer tissues B58 and B61 grown on NCP plates also exhibited similar drug sensitivity. These results were in good agreement with the conventional assay method using ATP quantification. We confirmed the antitumor effects of the drugs on cells seeded in 96-well plates using the BioStation CT imaging technique. We expect this method to be useful in research for new antitumor agents and for drug sensitivity tests in individually-tailored cancer treatments. © 2015 The Authors. Cancer Science published by Wiley Publishing Asia Pty Ltd on behalf of Japanese Cancer Association.

A digital ISO expansion technique for digital cameras

NASA Astrophysics Data System (ADS)

Yoo, Youngjin; Lee, Kangeui; Choe, Wonhee; Park, SungChan; Lee, Seong-Deok; Kim, Chang-Yong

2010-01-01

Market's demands of digital cameras for higher sensitivity capability under low-light conditions are remarkably increasing nowadays. The digital camera market is now a tough race for providing higher ISO capability. In this paper, we explore an approach for increasing maximum ISO capability of digital cameras without changing any structure of an image sensor or CFA. Our method is directly applied to the raw Bayer pattern CFA image to avoid non-linearity characteristics and noise amplification which are usually deteriorated after ISP (Image Signal Processor) of digital cameras. The proposed method fuses multiple short exposed images which are noisy, but less blurred. Our approach is designed to avoid the ghost artifact caused by hand-shaking and object motion. In order to achieve a desired ISO image quality, both low frequency chromatic noise and fine-grain noise that usually appear in high ISO images are removed and then we modify the different layers which are created by a two-scale non-linear decomposition of an image. Once our approach is performed on an input Bayer pattern CFA image, the resultant Bayer image is further processed by ISP to obtain a fully processed RGB image. The performance of our proposed approach is evaluated by comparing SNR (Signal to Noise Ratio), MTF50 (Modulation Transfer Function), color error ~E*ab and visual quality with reference images whose exposure times are properly extended into a variety of target sensitivity.

Reliable clarity automatic-evaluation method for optical remote sensing images

NASA Astrophysics Data System (ADS)

Qin, Bangyong; Shang, Ren; Li, Shengyang; Hei, Baoqin; Liu, Zhiwen

2015-10-01

Image clarity, which reflects the sharpness degree at the edge of objects in images, is an important quality evaluate index for optical remote sensing images. Scholars at home and abroad have done a lot of work on estimation of image clarity. At present, common clarity-estimation methods for digital images mainly include frequency-domain function methods, statistical parametric methods, gradient function methods and edge acutance methods. Frequency-domain function method is an accurate clarity-measure approach. However, its calculation process is complicate and cannot be carried out automatically. Statistical parametric methods and gradient function methods are both sensitive to clarity of images, while their results are easy to be affected by the complex degree of images. Edge acutance method is an effective approach for clarity estimate, while it needs picking out the edges manually. Due to the limits in accuracy, consistent or automation, these existing methods are not applicable to quality evaluation of optical remote sensing images. In this article, a new clarity-evaluation method, which is based on the principle of edge acutance algorithm, is proposed. In the new method, edge detection algorithm and gradient search algorithm are adopted to automatically search the object edges in images. Moreover, The calculation algorithm for edge sharpness has been improved. The new method has been tested with several groups of optical remote sensing images. Compared with the existing automatic evaluation methods, the new method perform better both in accuracy and consistency. Thus, the new method is an effective clarity evaluation method for optical remote sensing images.

Assessment of body fat based on potential function clustering segmentation of computed tomography images

NASA Astrophysics Data System (ADS)

Zhang, Lixin; Lin, Min; Wan, Baikun; Zhou, Yu; Wang, Yizhong

2005-01-01

In this paper, a new method of body fat and its distribution testing is proposed based on CT image processing. As it is more sensitive to slight differences in attenuation than standard radiography, CT depicts the soft tissues with better clarity. And body fat has a distinct grayness range compared with its neighboring tissues in a CT image. An effective multi-thresholds image segmentation method based on potential function clustering is used to deal with multiple peaks in the grayness histogram of a CT image. The CT images of abdomens of 14 volunteers with different fatness are processed with the proposed method. Not only can the result of total fat area be got, but also the differentiation of subcutaneous fat from intra-abdominal fat has been identified. The results show the adaptability and stability of the proposed method, which will be a useful tool for diagnosing obesity.

High PRF ultrafast sliding compound doppler imaging: fully qualitative and quantitative analysis of blood flow

NASA Astrophysics Data System (ADS)

Kang, Jinbum; Jang, Won Seuk; Yoo, Yangmo

2018-02-01

Ultrafast compound Doppler imaging based on plane-wave excitation (UCDI) can be used to evaluate cardiovascular diseases using high frame rates. In particular, it provides a fully quantifiable flow analysis over a large region of interest with high spatio-temporal resolution. However, the pulse-repetition frequency (PRF) in the UCDI method is limited for high-velocity flow imaging since it has a tradeoff between the number of plane-wave angles (N) and acquisition time. In this paper, we present high PRF ultrafast sliding compound Doppler imaging method (HUSDI) to improve quantitative flow analysis. With the HUSDI method, full scanline images (i.e. each tilted plane wave data) in a Doppler frame buffer are consecutively summed using a sliding window to create high-quality ensemble data so that there is no reduction in frame rate and flow sensitivity. In addition, by updating a new compounding set with a certain time difference (i.e. sliding window step size or L), the HUSDI method allows various Doppler PRFs with the same acquisition data to enable a fully qualitative, retrospective flow assessment. To evaluate the performance of the proposed HUSDI method, simulation, in vitro and in vivo studies were conducted under diverse flow circumstances. In the simulation and in vitro studies, the HUSDI method showed improved hemodynamic representations without reducing either temporal resolution or sensitivity compared to the UCDI method. For the quantitative analysis, the root mean squared velocity error (RMSVE) was measured using 9 angles (-12° to 12°) with L of 1-9, and the results were found to be comparable to those of the UCDI method (L  =  N  =  9), i.e.  ⩽0.24 cm s-1, for all L values. For the in vivo study, the flow data acquired from a full cardiac cycle of the femoral vessels of a healthy volunteer were analyzed using a PW spectrogram, and arterial and venous flows were successfully assessed with high Doppler PRF (e.g. 5 kHz at L  =  4). These results indicate that the proposed HUSDI method can improve flow visualization and quantification with a higher frame rate, PRF and flow sensitivity in cardiovascular imaging.

High PRF ultrafast sliding compound doppler imaging: fully qualitative and quantitative analysis of blood flow.

PubMed

Kang, Jinbum; Jang, Won Seuk; Yoo, Yangmo

2018-02-09

Ultrafast compound Doppler imaging based on plane-wave excitation (UCDI) can be used to evaluate cardiovascular diseases using high frame rates. In particular, it provides a fully quantifiable flow analysis over a large region of interest with high spatio-temporal resolution. However, the pulse-repetition frequency (PRF) in the UCDI method is limited for high-velocity flow imaging since it has a tradeoff between the number of plane-wave angles (N) and acquisition time. In this paper, we present high PRF ultrafast sliding compound Doppler imaging method (HUSDI) to improve quantitative flow analysis. With the HUSDI method, full scanline images (i.e. each tilted plane wave data) in a Doppler frame buffer are consecutively summed using a sliding window to create high-quality ensemble data so that there is no reduction in frame rate and flow sensitivity. In addition, by updating a new compounding set with a certain time difference (i.e. sliding window step size or L), the HUSDI method allows various Doppler PRFs with the same acquisition data to enable a fully qualitative, retrospective flow assessment. To evaluate the performance of the proposed HUSDI method, simulation, in vitro and in vivo studies were conducted under diverse flow circumstances. In the simulation and in vitro studies, the HUSDI method showed improved hemodynamic representations without reducing either temporal resolution or sensitivity compared to the UCDI method. For the quantitative analysis, the root mean squared velocity error (RMSVE) was measured using 9 angles (-12° to 12°) with L of 1-9, and the results were found to be comparable to those of the UCDI method (L  =  N  =  9), i.e.  ⩽0.24 cm s -1 , for all L values. For the in vivo study, the flow data acquired from a full cardiac cycle of the femoral vessels of a healthy volunteer were analyzed using a PW spectrogram, and arterial and venous flows were successfully assessed with high Doppler PRF (e.g. 5 kHz at L  =  4). These results indicate that the proposed HUSDI method can improve flow visualization and quantification with a higher frame rate, PRF and flow sensitivity in cardiovascular imaging.

Quantitative digital image analysis of chromogenic assays for high throughput screening of alpha-amylase mutant libraries.

PubMed

Shankar, Manoharan; Priyadharshini, Ramachandran; Gunasekaran, Paramasamy

2009-08-01

An image analysis-based method for high throughput screening of an alpha-amylase mutant library using chromogenic assays was developed. Assays were performed in microplates and high resolution images of the assay plates were read using the Virtual Microplate Reader (VMR) script to quantify the concentration of the chromogen. This method is fast and sensitive in quantifying 0.025-0.3 mg starch/ml as well as 0.05-0.75 mg glucose/ml. It was also an effective screening method for improved alpha-amylase activity with a coefficient of variance of 18%.

Simulated electronic heterodyne recording and processing of pulsed-laser holograms

NASA Technical Reports Server (NTRS)

Decker, A. J.

1979-01-01

The electronic recording of pulsed-laser holograms is proposed. The polarization sensitivity of each resolution element of the detector is controlled independently to add an arbitrary phase to the image waves. This method which can be used to simulate heterodyne recording and to process three-dimensional optical images, is based on a similar method for heterodyne recording and processing of continuous-wave holograms.

Review of photoacoustic flow imaging: its current state and its promises

PubMed Central

van den Berg, P.J.; Daoudi, K.; Steenbergen, W.

2015-01-01

Flow imaging is an important method for quantification in many medical imaging modalities, with applications ranging from estimating wall shear rate to detecting angiogenesis. Modalities like ultrasound and optical coherence tomography both offer flow imaging capabilities, but suffer from low contrast to red blood cells and are sensitive to clutter artefacts. Photoacoustic imaging (PAI) is a relatively new field, with a recent interest in flow imaging. The recent enthusiasm for PA flow imaging is due to its intrinsic contrast to haemoglobin, which offers a new spin on existing methods of flow imaging, and some unique approaches in addition. This review article will delve into the research on photoacoustic flow imaging, explain the principles behind the many techniques and comment on their individual advantages and disadvantages. PMID:26640771

Review of photoacoustic flow imaging: its current state and its promises.

PubMed

van den Berg, P J; Daoudi, K; Steenbergen, W

2015-09-01

Flow imaging is an important method for quantification in many medical imaging modalities, with applications ranging from estimating wall shear rate to detecting angiogenesis. Modalities like ultrasound and optical coherence tomography both offer flow imaging capabilities, but suffer from low contrast to red blood cells and are sensitive to clutter artefacts. Photoacoustic imaging (PAI) is a relatively new field, with a recent interest in flow imaging. The recent enthusiasm for PA flow imaging is due to its intrinsic contrast to haemoglobin, which offers a new spin on existing methods of flow imaging, and some unique approaches in addition. This review article will delve into the research on photoacoustic flow imaging, explain the principles behind the many techniques and comment on their individual advantages and disadvantages.

Photoacoustic microscopy of human teeth

NASA Astrophysics Data System (ADS)

Rao, Bin; Cai, Xin; Favazza, Christopher; Yao, Junjie; Li, Li; Duong, Steven; Liaw, Lih-Huei; Holtzman, Jennifer; Wilder-Smith, Petra; Wang, Lihong V.

2011-03-01

Photoacoustic microscopy (PAM) utilizes short laser pulses to deposit energy into light absorbers and sensitively detects the ultrasonic waves the absorbers generate in response. PAM directly renders a three-dimensional spatial distribution of sub-surface optical absorbers. Unlike other optical imaging technologies, PAM features label-free optical absorption contrast and excellent imaging depths. Standard dental imaging instruments are limited to X-ray and CCD cameras. Subsurface optical dental imaging is difficult due to the highly-scattering enamel and dentin tissue. Thus, very few imaging methods can detect dental decay or diagnose dental pulp, which is the innermost part of the tooth, containing the nerves, blood vessels, and other cells. Here, we conducted a feasibility study on imaging dental decay and dental pulp with PAM. Our results showed that PAM is sensitive to the color change associated with dental decay. Although the relative PA signal distribution may be affected by surface contours and subsurface reflections from deeper dental tissue, monitoring changes in the PA signals (at the same site) over time is necessary to identify the progress of dental decay. Our results also showed that deep-imaging, near-infrared (NIR) PAM can sensitively image blood in the dental pulp of an in vitro tooth. In conclusion, PAM is a promising tool for imaging both dental decay and dental pulp.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gilbert, Andrew J.; Miller, Brian W.; Robinson, Sean M.

Imaging technology is generally considered too invasive for arms control inspections due to the concern that it cannot properly secure sensitive features of the inspected item. However, this same sensitive information, which could include direct information on the form and function of the items under inspection, could be used for robust arms control inspections. The single-pixel X-ray imager (SPXI) is introduced as a method to make such inspections, capturing the salient spatial information of an object in a secure manner while never forming an actual image. The method is built on the theory of compressive sensing and the single pixelmore » optical camera. The performance of the system is quantified here using simulated inspections of simple objects. Measures of the robustness and security of the method are introduced and used to determine how such an inspection would be made which can maintain high robustness and security. In particular, it is found that an inspection with low noise (<1%) and high undersampling (>256×) exhibits high robustness and security.« less

Quantitative Ultrasound for Measuring Obstructive Severity in Children with Hydronephrosis.

PubMed

Cerrolaza, Juan J; Peters, Craig A; Martin, Aaron D; Myers, Emmarie; Safdar, Nabile; Linguraru, Marius George

2016-04-01

We define sonographic biomarkers for hydronephrotic renal units that can predict the necessity of diuretic nuclear renography. We selected a cohort of 50 consecutive patients with hydronephrosis of varying severity in whom 2-dimensional sonography and diuretic mercaptoacetyltriglycine renography had been performed. A total of 131 morphological parameters were computed using quantitative image analysis algorithms. Machine learning techniques were then applied to identify ultrasound based safety thresholds that agreed with the t½ for washout. A best fit model was then derived for each threshold level of t½ that would be clinically relevant at 20, 30 and 40 minutes. Receiver operating characteristic curve analysis was performed. Sensitivity, specificity and area under the receiver operating characteristic curve were determined. Improvement obtained by the quantitative imaging method compared to the Society for Fetal Urology grading system and the hydronephrosis index was statistically verified. For the 3 thresholds considered and at 100% sensitivity the specificities of the quantitative imaging method were 94%, 70% and 74%, respectively. Corresponding area under the receiver operating characteristic curve values were 0.98, 0.94 and 0.94, respectively. Improvement obtained by the quantitative imaging method over the Society for Fetal Urology grade and hydronephrosis index was statistically significant (p <0.05 in all cases). Quantitative imaging analysis of renal sonograms in children with hydronephrosis can identify thresholds of clinically significant washout times with 100% sensitivity to decrease the number of diuretic renograms in up to 62% of children. Copyright © 2016 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.

Classification of skin cancer images using local binary pattern and SVM classifier

NASA Astrophysics Data System (ADS)

Adjed, Faouzi; Faye, Ibrahima; Ababsa, Fakhreddine; Gardezi, Syed Jamal; Dass, Sarat Chandra

2016-11-01

In this paper, a classification method for melanoma and non-melanoma skin cancer images has been presented using the local binary patterns (LBP). The LBP computes the local texture information from the skin cancer images, which is later used to compute some statistical features that have capability to discriminate the melanoma and non-melanoma skin tissues. Support vector machine (SVM) is applied on the feature matrix for classification into two skin image classes (malignant and benign). The method achieves good classification accuracy of 76.1% with sensitivity of 75.6% and specificity of 76.7%.

Combined two-dimensional velocity and temperature measurements of natural convection using a high-speed camera and temperature-sensitive particles

NASA Astrophysics Data System (ADS)

Someya, Satoshi; Li, Yanrong; Ishii, Keiko; Okamoto, Koji

2011-01-01

This paper proposes a combined method for two-dimensional temperature and velocity measurements in liquid and gas flows using temperature-sensitive particles (TSPs), a pulsed ultraviolet laser, and a high-speed camera. TSPs respond to temperature changes in the flow and can also serve as tracers for the velocity field. The luminescence from the TSPs was recorded at 15,000 frames per second as sequential images for a lifetime-based temperature analysis. These images were also used for the particle image velocimetry calculations. The temperature field was estimated using several images, based on the lifetime method. The decay curves for various temperature conditions fit well to exponential functions, and from these the decay constants at each temperature were obtained. The proposed technique was applied to measure the temperature and velocity fields in natural convection driven by a Marangoni force and buoyancy in a rectangular tank. The accuracy of the temperature measurement of the proposed technique was ±0.35-0.40°C.

Segmentation of epidermal tissue with histopathological damage in images of haematoxylin and eosin stained human skin

PubMed Central

2014-01-01

Background Digital image analysis has the potential to address issues surrounding traditional histological techniques including a lack of objectivity and high variability, through the application of quantitative analysis. A key initial step in image analysis is the identification of regions of interest. A widely applied methodology is that of segmentation. This paper proposes the application of image analysis techniques to segment skin tissue with varying degrees of histopathological damage. The segmentation of human tissue is challenging as a consequence of the complexity of the tissue structures and inconsistencies in tissue preparation, hence there is a need for a new robust method with the capability to handle the additional challenges materialising from histopathological damage. Methods A new algorithm has been developed which combines enhanced colour information, created following a transformation to the L*a*b* colourspace, with general image intensity information. A colour normalisation step is included to enhance the algorithm’s robustness to variations in the lighting and staining of the input images. The resulting optimised image is subjected to thresholding and the segmentation is fine-tuned using a combination of morphological processing and object classification rules. The segmentation algorithm was tested on 40 digital images of haematoxylin & eosin (H&E) stained skin biopsies. Accuracy, sensitivity and specificity of the algorithmic procedure were assessed through the comparison of the proposed methodology against manual methods. Results Experimental results show the proposed fully automated methodology segments the epidermis with a mean specificity of 97.7%, a mean sensitivity of 89.4% and a mean accuracy of 96.5%. When a simple user interaction step is included, the specificity increases to 98.0%, the sensitivity to 91.0% and the accuracy to 96.8%. The algorithm segments effectively for different severities of tissue damage. Conclusions Epidermal segmentation is a crucial first step in a range of applications including melanoma detection and the assessment of histopathological damage in skin. The proposed methodology is able to segment the epidermis with different levels of histological damage. The basic method framework could be applied to segmentation of other epithelial tissues. PMID:24521154

Experimental investigation of a HOPG crystal fan for x-ray fluorescence molecular imaging

NASA Astrophysics Data System (ADS)

Rosentreter, Tanja; Müller, Bernhard; Schlattl, Helmut; Hoeschen, Christoph

2017-03-01

Imaging x-ray fluorescence generally generates a conflict between the best image quality or highest sensitivity and lowest possible radiation dose. Consequently many experimental studies investigating the feasibility of this molecular imaging method, deal with either monochromatic x-ray sources that are not practical in clinical environment or accept high x-ray doses in order to maintain the advantage of high sensitivity and producing high quality images. In this work we present a x-ray fluorescence imaging setup using a HOPG crystal fan construction consisting of a Bragg reflecting analyzer array together with a scatter reducing radial collimator. This method allows for the use of polychromatic x-ray tubes that are in general easily accessible in contrast to monochromatic x-ray sources such as synchrotron facilities. Moreover this energy-selecting device minimizes the amount of Compton scattered photons while simultaneously increasing the fluorescence signal yield, thus significantly reducing the signal to noise ratio. The aim is to show the feasibility of this approach by measuring the Bragg reflected Kα fluorescence signal of an object containing an iodine solution using a large area detector with moderate energy resolution. Contemplating the anisotropic energy distribution of background scattered x-rays we compare the detection sensitivity, applying two different detector angular configurations. Our results show that even for large area detectors with limited energy resolution, iodine concentrations of 0.12 % can be detected. However, the potentially large scan times and therefore high radiation dose need to be decreased in further investigations.

Diagnosis of Tempromandibular Disorders Using Local Binary Patterns

PubMed Central

Haghnegahdar, A.A.; Kolahi, S.; Khojastepour, L.; Tajeripour, F.

2018-01-01

Background: Temporomandibular joint disorder (TMD) might be manifested as structural changes in bone through modification, adaptation or direct destruction. We propose to use Local Binary Pattern (LBP) characteristics and histogram-oriented gradients on the recorded images as a diagnostic tool in TMD assessment. Material and Methods: CBCT images of 66 patients (132 joints) with TMD and 66 normal cases (132 joints) were collected and 2 coronal cut prepared from each condyle, although images were limited to head of mandibular condyle. In order to extract features of images, first we use LBP and then histogram of oriented gradients. To reduce dimensionality, the linear algebra Singular Value Decomposition (SVD) is applied to the feature vectors matrix of all images. For evaluation, we used K nearest neighbor (K-NN), Support Vector Machine, Naïve Bayesian and Random Forest classifiers. We used Receiver Operating Characteristic (ROC) to evaluate the hypothesis. Results: K nearest neighbor classifier achieves a very good accuracy (0.9242), moreover, it has desirable sensitivity (0.9470) and specificity (0.9015) results, when other classifiers have lower accuracy, sensitivity and specificity. Conclusion: We proposed a fully automatic approach to detect TMD using image processing techniques based on local binary patterns and feature extraction. K-NN has been the best classifier for our experiments in detecting patients from healthy individuals, by 92.42% accuracy, 94.70% sensitivity and 90.15% specificity. The proposed method can help automatically diagnose TMD at its initial stages. PMID:29732343

Correction of motion artefacts and pseudo colour visualization of multispectral light scattering images for optical diagnosis of rheumatoid arthritis

NASA Astrophysics Data System (ADS)

Minet, Olaf; Scheibe, Patrick; Beuthan, Jürgen; Zabarylo, Urszula

2009-10-01

State-of-the-art image processing methods offer new possibilities for diagnosing diseases using scattered light. The optical diagnosis of rheumatism is taken as an example to show that the diagnostic sensitivity can be improved using overlapped pseudo-coloured images of different wavelengths, provided that multispectral images are recorded to compensate for any motion related artefacts which occur during examination.

Correction of motion artefacts and pseudo colour visualization of multispectral light scattering images for optical diagnosis of rheumatoid arthritis

NASA Astrophysics Data System (ADS)

Minet, Olaf; Scheibe, Patrick; Beuthan, Jürgen; Zabarylo, Urszula

2010-02-01

State-of-the-art image processing methods offer new possibilities for diagnosing diseases using scattered light. The optical diagnosis of rheumatism is taken as an example to show that the diagnostic sensitivity can be improved using overlapped pseudo-coloured images of different wavelengths, provided that multispectral images are recorded to compensate for any motion related artefacts which occur during examination.

Deep-tissue reporter-gene imaging with fluorescence and optoacoustic tomography: a performance overview.

PubMed

Deliolanis, Nikolaos C; Ale, Angelique; Morscher, Stefan; Burton, Neal C; Schaefer, Karin; Radrich, Karin; Razansky, Daniel; Ntziachristos, Vasilis

2014-10-01

A primary enabling feature of near-infrared fluorescent proteins (FPs) and fluorescent probes is the ability to visualize deeper in tissues than in the visible. The purpose of this work is to find which is the optimal visualization method that can exploit the advantages of this novel class of FPs in full-scale pre-clinical molecular imaging studies. Nude mice were stereotactically implanted with near-infrared FP expressing glioma cells to from brain tumors. The feasibility and performance metrics of FPs were compared between planar epi-illumination and trans-illumination fluorescence imaging, as well as to hybrid Fluorescence Molecular Tomography (FMT) system combined with X-ray CT and Multispectral Optoacoustic (or Photoacoustic) Tomography (MSOT). It is shown that deep-seated glioma brain tumors are possible to visualize both with fluorescence and optoacoustic imaging. Fluorescence imaging is straightforward and has good sensitivity; however, it lacks resolution. FMT-XCT can provide an improved rough resolution of ∼1 mm in deep tissue, while MSOT achieves 0.1 mm resolution in deep tissue and has comparable sensitivity. We show imaging capacity that can shift the visualization paradigm in biological discovery. The results are relevant not only to reporter gene imaging, but stand as cross-platform comparison for all methods imaging near infrared fluorescent contrast agents.

Engineering Gd-loaded nanoparticles to enhance MRI sensitivity via T1 shortening

NASA Astrophysics Data System (ADS)

Bruckman, Michael A.; Yu, Xin; Steinmetz, Nicole F.

2013-11-01

Magnetic resonance imaging (MRI) is a noninvasive imaging technique capable of obtaining high-resolution anatomical images of the body. Major drawbacks of MRI are the low contrast agent sensitivity and inability to distinguish healthy tissue from diseased tissue, making early detection challenging. To address this technological hurdle, paramagnetic contrast agents have been developed to increase the longitudinal relaxivity, leading to an increased signal-to-noise ratio. This review focuses on methods and principles that enabled the design and engineering of nanoparticles to deliver contrast agents with enhanced ionic relaxivities. Different engineering strategies and nanoparticle platforms will be compared in terms of their manufacturability, biocompatibility properties, and their overall potential to make an impact in clinical MR imaging.

Relationships between Visual Field Sensitivity and Spectral Absorption Properties of the Neuroretinal Rim in Glaucoma by Multispectral Imaging

PubMed Central

Denniss, Jonathan; Schiessl, Ingo; Nourrit, Vincent; Fenerty, Cecilia H.; Gautam, Ramesh; Henson, David B.

2011-01-01

Purpose. To investigate the relationship between neuroretinal rim (NRR) differential light absorption (DLA, a measure of spectral absorption properties) and visual field (VF) sensitivity in primary open-angle glaucoma (POAG). Methods. Patients diagnosed with (n = 22) or suspected of having (n = 7) POAG were imaged with a multispectral system incorporating a modified digital fundus camera, 250-W tungsten-halogen lamp, and fast-tuneable liquid crystal filter. Five images were captured sequentially within 1.0 second at wavelengths selected according to absorption properties of hemoglobin (range, 570–610 nm), and a Beer-Lambert law model was used to produce DLA maps of residual NRR from the images. Patients also underwent VF testing. Differences in NRR DLA in vertically opposing 180° and 45° sectors either side of the horizontal midline were compared with corresponding differences in VF sensitivity on both decibel and linear scales by Spearman's rank correlation. Results. The decibel VF sensitivity scale showed significant relationships between superior–inferior NRR DLA difference and sensitivity differences between corresponding VF areas in 180° NRR sectors (Spearman ρ = 0.68; P < 0.0001), superior-/inferior-temporal 45° NRR sectors (ρ = 0.57; P < 0.002), and superior-/inferior-nasal 45° NRR sectors (ρ = 0.59; P < 0.001). Using the linear VF sensitivity scale significant relationships were found for 180° NRR sectors (ρ = 0.62; P < 0.0002) and superior–inferior–nasal 45° NRR sectors (ρ = 0.53; P < 0.002). No significant difference was found between correlations using the linear or decibel VF sensitivity scales. Conclusions. Residual NRR DLA is related to VF sensitivity in POAG. Multispectral imaging may provide clinically important information for the assessment and management of POAG. PMID:21980002

Clinical utility of capsule endoscopy with flexible spectral imaging color enhancement for diagnosis of small bowel lesions

PubMed Central

Sato, Yasushi; Sagawa, Tamotsu; Hirakawa, Masahiro; Ohnuma, Hiroyuki; Osuga, Takahiro; Okagawa, Yutaka; Tamura, Fumito; Horiguchi, Hiroto; Takada, Kohichi; Hayashi, Tsuyoshi; Sato, Tsutomu; Miyanishi, Koji; Takimoto, Rishu; Kobune, Masayoshi; Kato, Junji

2014-01-01

Background and study aims: The clinical utility of computed virtual chromoendoscopy with flexible spectral imaging color enhancement (FICE) in capsule endoscopy (CE) remains controversial. To clarify the clinical utility of FICE-enhanced CE in evaluating small bowel lesions, we quantitatively assessed white light (WL), FICE, and blue mode (BM) images and examined the sensitivity of these 3 imaging modes of small-bowel lesions from patients who underwent CE. Methods: The CIELAB color difference (∆E) and visual analogue scales (VAS) were measured in 261 CE images (3 different lesion categories) using WL and FICE set 1, 2, and 3, and BM images, respectively. Three endoscopists reviewed CE videos with WL, 3 FICE mode settings, and BM, and compared the sensitivity and detectability for small intestinal diseases from 50 patients who underwent CE. Results: In the assessment of visibility in the 152 vascular lesion images, the ∆E and VAS of FICE set 1, 2, and BM images were significantly higher than that of WL images. In 88 erosion/ulceration images, the ∆E and VAS of FICE set 1 and 2 images were significantly higher than that of WL images. In 21 tumor images, there were no significant differences in ∆E among these modalities. When analyzed on a per-patient basis, FICE settings 1 and 2 had the highest sensitivity (100 %) and specificity (97.3 – 100 %) for vascular lesions. As for erosive/ulcerative lesions, FICE setting 2 had the highest sensitivity (100 %) and specificity (97.2 %). For tumors or polyps, WL had the highest sensitivity (90.9 %) and specificity (87.1 %). In per-lesion analysis, FICE settings 1 and 2 showed significantly superior detection ability over WL for vascular lesions. In the detection of erosive/ulcerative lesions, FICE setting 2 was significantly superior to WL. In tumor images, there was no significant improvement with any of the settings relative to WL images. Conclusions: FICE is most useful for improving CE image quality and detection in cases of angioectasia and erosion/ulceration of the small intestine. PMID:26135265

RECONSTRUCTION OF DYNAMIC IMAGE SERIES FROM UNDERSAMPLED MRI DATA USING DATA-DRIVEN MODEL CONSISTENCY CONDITION (MOCCO)

PubMed Central

Velikina, Julia V.; Samsonov, Alexey A.

2014-01-01

Purpose To accelerate dynamic MR imaging through development of a novel image reconstruction technique using low-rank temporal signal models pre-estimated from training data. Theory We introduce the MOdel Consistency COndition (MOCCO) technique that utilizes temporal models to regularize the reconstruction without constraining the solution to be low-rank as performed in related techniques. This is achieved by using a data-driven model to design a transform for compressed sensing-type regularization. The enforcement of general compliance with the model without excessively penalizing deviating signal allows recovery of a full-rank solution. Methods Our method was compared to standard low-rank approach utilizing model-based dimensionality reduction in phantoms and patient examinations for time-resolved contrast-enhanced angiography (CE MRA) and cardiac CINE imaging. We studied sensitivity of all methods to rank-reduction and temporal subspace modeling errors. Results MOCCO demonstrated reduced sensitivity to modeling errors compared to the standard approach. Full-rank MOCCO solutions showed significantly improved preservation of temporal fidelity and aliasing/noise suppression in highly accelerated CE MRA (acceleration up to 27) and cardiac CINE (acceleration up to 15) data. Conclusions MOCCO overcomes several important deficiencies of previously proposed methods based on pre-estimated temporal models and allows high quality image restoration from highly undersampled CE-MRA and cardiac CINE data. PMID:25399724

SU-E-J-142: Performance Study of Automatic Image-Segmentation Algorithms in Motion Tracking Via MR-IGRT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Feng, Y; Olsen, J.; Parikh, P.

2014-06-01

Purpose: Evaluate commonly used segmentation algorithms on a commercially available real-time MR image guided radiotherapy (MR-IGRT) system (ViewRay), compare the strengths and weaknesses of each method, with the purpose of improving motion tracking for more accurate radiotherapy. Methods: MR motion images of bladder, kidney, duodenum, and liver tumor were acquired for three patients using a commercial on-board MR imaging system and an imaging protocol used during MR-IGRT. A series of 40 frames were selected for each case to cover at least 3 respiratory cycles. Thresholding, Canny edge detection, fuzzy k-means (FKM), k-harmonic means (KHM), and reaction-diffusion level set evolution (RD-LSE),more » along with the ViewRay treatment planning and delivery system (TPDS) were included in the comparisons. To evaluate the segmentation results, an expert manual contouring of the organs or tumor from a physician was used as a ground-truth. Metrics value of sensitivity, specificity, Jaccard similarity, and Dice coefficient were computed for comparison. Results: In the segmentation of single image frame, all methods successfully segmented the bladder and kidney, but only FKM, KHM and TPDS were able to segment the liver tumor and the duodenum. For segmenting motion image series, the TPDS method had the highest sensitivity, Jarccard, and Dice coefficients in segmenting bladder and kidney, while FKM and KHM had a slightly higher specificity. A similar pattern was observed when segmenting the liver tumor and the duodenum. The Canny method is not suitable for consistently segmenting motion frames in an automated process, while thresholding and RD-LSE cannot consistently segment a liver tumor and the duodenum. Conclusion: The study compared six different segmentation methods and showed the effectiveness of the ViewRay TPDS algorithm in segmenting motion images during MR-IGRT. Future studies include a selection of conformal segmentation methods based on image/organ-specific information, different filtering methods and their influences on the segmentation results. Parag Parikh receives research grant from ViewRay. Sasa Mutic has consulting and research agreements with ViewRay. Yanle Hu receives travel reimbursement from ViewRay. Iwan Kawrakow and James Dempsey are ViewRay employees.« less

Nondestructive Analysis of Tumor-Associated Membrane Protein Integrating Imaging and Amplified Detection in situ Based on Dual-Labeled DNAzyme.

PubMed

Chen, Xiaoxia; Zhao, Jing; Chen, Tianshu; Gao, Tao; Zhu, Xiaoli; Li, Genxi

2018-01-01

Comprehensive analysis of the expression level and location of tumor-associated membrane proteins (TMPs) is of vital importance for the profiling of tumor cells. Currently, two kinds of independent techniques, i.e. ex situ detection and in situ imaging, are usually required for the quantification and localization of TMPs respectively, resulting in some inevitable problems. Methods: Herein, based on a well-designed and fluorophore-labeled DNAzyme, we develop an integrated and facile method, in which imaging and quantification of TMPs in situ are achieved simultaneously in a single system. The labeled DNAzyme not only produces localized fluorescence for the visualization of TMPs but also catalyzes the cleavage of a substrate to produce quantitative fluorescent signals that can be collected from solution for the sensitive detection of TMPs. Results: Results from the DNAzyme-based in situ imaging and quantification of TMPs match well with traditional immunofluorescence and western blotting. In addition to the advantage of two-in-one, the DNAzyme-based method is highly sensitivity, allowing the detection of TMPs in only 100 cells. Moreover, the method is nondestructive. Cells after analysis could retain their physiological activity and could be cultured for other applications. Conclusion: The integrated system provides solid results for both imaging and quantification of TMPs, making it a competitive method over some traditional techniques for the analysis of TMPs, which offers potential application as a toolbox in the future.

Imaging voltage in neurons

PubMed Central

Peterka, Darcy S.; Takahashi, Hiroto; Yuste, Rafael

2011-01-01

In the last decades, imaging membrane potential has become a fruitful approach to study neural circuits, especially in invertebrate preparations with large, resilient neurons. At the same time, particularly in mammalian preparations, voltage imaging methods suffer from poor signal to noise and secondary side effects, and they fall short of providing single-cell resolution when imaging of the activity of neuronal populations. As an introduction to these techniques, we briefly review different voltage imaging methods (including organic fluorophores, SHG chromophores, genetic indicators, hybrid, nanoparticles and intrinsic approaches), and illustrate some of their applications to neuronal biophysics and mammalian circuit analysis. We discuss their mechanisms of voltage sensitivity, from reorientation, electrochromic or electro-optical phenomena, to interaction among chromophores or membrane scattering, and highlight their advantages and shortcomings, commenting on the outlook for development of novel voltage imaging methods. PMID:21220095

A cable-driven parallel manipulator with force sensing capabilities for high-accuracy tissue endomicroscopy.

PubMed

Miyashita, Kiyoteru; Oude Vrielink, Timo; Mylonas, George

2018-05-01

Endomicroscopy (EM) provides high resolution, non-invasive histological tissue information and can be used for scanning of large areas of tissue to assess cancerous and pre-cancerous lesions and their margins. However, current robotic solutions do not provide the accuracy and force sensitivity required to perform safe and accurate tissue scanning. A new surgical instrument has been developed that uses a cable-driven parallel mechanism (CPDM) to manipulate an EM probe. End-effector forces are determined by measuring the tensions in each cable. As a result, the instrument allows to accurately apply a contact force on a tissue, while at the same time offering high resolution and highly repeatable probe movement. 0.2 and 0.6 N force sensitivities were found for 1 and 2 DoF image acquisition methods, respectively. A back-stepping technique can be used when a higher force sensitivity is required for the acquisition of high quality tissue images. This method was successful in acquiring images on ex vivo liver tissue. The proposed approach offers high force sensitivity and precise control, which is essential for robotic EM. The technical benefits of the current system can also be used for other surgical robotic applications, including safe autonomous control, haptic feedback and palpation.

Atomic bonding effects in annular dark field scanning transmission electron microscopy. I. Computational predictions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Odlyzko, Michael L.; Mkhoyan, K. Andre, E-mail: mkhoyan@umn.edu; Himmetoglu, Burak

2016-07-15

Annular dark field scanning transmission electron microscopy (ADF-STEM) image simulations were performed for zone-axis-oriented light-element single crystals, using a multislice method adapted to include charge redistribution due to chemical bonding. Examination of these image simulations alongside calculations of the propagation of the focused electron probe reveal that the evolution of the probe intensity with thickness exhibits significant sensitivity to interatomic charge transfer, accounting for observed thickness-dependent bonding sensitivity of contrast in all ADF-STEM imaging conditions. Because changes in image contrast relative to conventional neutral atom simulations scale directly with the net interatomic charge transfer, the strongest effects are seen inmore » crystals with highly polar bonding, while no effects are seen for nonpolar bonding. Although the bonding dependence of ADF-STEM image contrast varies with detector geometry, imaging parameters, and material temperature, these simulations predict the bonding effects to be experimentally measureable.« less

Dark-field hyperspectral X-ray imaging

PubMed Central

Egan, Christopher K.; Jacques, Simon D. M.; Connolley, Thomas; Wilson, Matthew D.; Veale, Matthew C.; Seller, Paul; Cernik, Robert J.

2014-01-01

In recent times, there has been a drive to develop non-destructive X-ray imaging techniques that provide chemical or physical insight. To date, these methods have generally been limited; either requiring raster scanning of pencil beams, using narrow bandwidth radiation and/or limited to small samples. We have developed a novel full-field radiographic imaging technique that enables the entire physio-chemical state of an object to be imaged in a single snapshot. The method is sensitive to emitted and scattered radiation, using a spectral imaging detector and polychromatic hard X-radiation, making it particularly useful for studying large dense samples for materials science and engineering applications. The method and its extension to three-dimensional imaging is validated with a series of test objects and demonstrated to directly image the crystallographic preferred orientation and formed precipitates across an aluminium alloy friction stir weld section. PMID:24808753

Wideband optical sensing using pulse interferometry.

PubMed

Rosenthal, Amir; Razansky, Daniel; Ntziachristos, Vasilis

2012-08-13

Advances in fabrication of high-finesse optical resonators hold promise for the development of miniaturized, ultra-sensitive, wide-band optical sensors, based on resonance-shift detection. Many potential applications are foreseen for such sensors, among them highly sensitive detection in ultrasound and optoacoustic imaging. Traditionally, sensor interrogation is performed by tuning a narrow linewidth laser to the resonance wavelength. Despite the ubiquity of this method, its use has been mostly limited to lab conditions due to its vulnerability to environmental factors and the difficulty of multiplexing - a key factor in imaging applications. In this paper, we develop a new optical-resonator interrogation scheme based on wideband pulse interferometry, potentially capable of achieving high stability against environmental conditions without compromising sensitivity. Additionally, the method can enable multiplexing several sensors. The unique properties of the pulse-interferometry interrogation approach are studied theoretically and experimentally. Methods for noise reduction in the proposed scheme are presented and experimentally demonstrated, while the overall performance is validated for broadband optical detection of ultrasonic fields. The achieved sensitivity is equivalent to the theoretical limit of a 6 MHz narrow-line width laser, which is 40 times higher than what can be usually achieved by incoherent interferometry for the same optical resonator.

Colorization-Based RGB-White Color Interpolation using Color Filter Array with Randomly Sampled Pattern

PubMed Central

Oh, Paul; Lee, Sukho; Kang, Moon Gi

2017-01-01

Recently, several RGB-White (RGBW) color filter arrays (CFAs) have been proposed, which have extra white (W) pixels in the filter array that are highly sensitive. Due to the high sensitivity, the W pixels have better SNR (Signal to Noise Ratio) characteristics than other color pixels in the filter array, especially, in low light conditions. However, most of the RGBW CFAs are designed so that the acquired RGBW pattern image can be converted into the conventional Bayer pattern image, which is then again converted into the final color image by using conventional demosaicing methods, i.e., color interpolation techniques. In this paper, we propose a new RGBW color filter array based on a totally different color interpolation technique, the colorization algorithm. The colorization algorithm was initially proposed for colorizing a gray image into a color image using a small number of color seeds. Here, we adopt this algorithm as a color interpolation technique, so that the RGBW color filter array can be designed with a very large number of W pixels to make the most of the highly sensitive characteristics of the W channel. The resulting RGBW color filter array has a pattern with a large proportion of W pixels, while the small-numbered RGB pixels are randomly distributed over the array. The colorization algorithm makes it possible to reconstruct the colors from such a small number of RGB values. Due to the large proportion of W pixels, the reconstructed color image has a high SNR value, especially higher than those of conventional CFAs in low light condition. Experimental results show that many important information which are not perceived in color images reconstructed with conventional CFAs are perceived in the images reconstructed with the proposed method. PMID:28657602

Colorization-Based RGB-White Color Interpolation using Color Filter Array with Randomly Sampled Pattern.

PubMed

Oh, Paul; Lee, Sukho; Kang, Moon Gi

2017-06-28

Recently, several RGB-White (RGBW) color filter arrays (CFAs) have been proposed, which have extra white (W) pixels in the filter array that are highly sensitive. Due to the high sensitivity, the W pixels have better SNR (Signal to Noise Ratio) characteristics than other color pixels in the filter array, especially, in low light conditions. However, most of the RGBW CFAs are designed so that the acquired RGBW pattern image can be converted into the conventional Bayer pattern image, which is then again converted into the final color image by using conventional demosaicing methods, i.e., color interpolation techniques. In this paper, we propose a new RGBW color filter array based on a totally different color interpolation technique, the colorization algorithm. The colorization algorithm was initially proposed for colorizing a gray image into a color image using a small number of color seeds. Here, we adopt this algorithm as a color interpolation technique, so that the RGBW color filter array can be designed with a very large number of W pixels to make the most of the highly sensitive characteristics of the W channel. The resulting RGBW color filter array has a pattern with a large proportion of W pixels, while the small-numbered RGB pixels are randomly distributed over the array. The colorization algorithm makes it possible to reconstruct the colors from such a small number of RGB values. Due to the large proportion of W pixels, the reconstructed color image has a high SNR value, especially higher than those of conventional CFAs in low light condition. Experimental results show that many important information which are not perceived in color images reconstructed with conventional CFAs are perceived in the images reconstructed with the proposed method.

Sensitivity of an Elekta iView GT a-Si EPID model to delivery errors for pre-treatment verification of IMRT fields.

PubMed

Herwiningsih, Sri; Hanlon, Peta; Fielding, Andrew

2014-12-01

A Monte Carlo model of an Elekta iViewGT amorphous silicon electronic portal imaging device (a-Si EPID) has been validated for pre-treatment verification of clinical IMRT treatment plans. The simulations involved the use of the BEAMnrc and DOSXYZnrc Monte Carlo codes to predict the response of the iViewGT a-Si EPID model. The predicted EPID images were compared to the measured images obtained from the experiment. The measured EPID images were obtained by delivering a photon beam from an Elekta Synergy linac to the Elekta iViewGT a-Si EPID. The a-Si EPID was used with no additional build-up material. Frame averaged EPID images were acquired and processed using in-house software. The agreement between the predicted and measured images was analyzed using the gamma analysis technique with acceptance criteria of 3 %/3 mm. The results show that the predicted EPID images for four clinical IMRT treatment plans have a good agreement with the measured EPID signal. Three prostate IMRT plans were found to have an average gamma pass rate of more than 95.0 % and a spinal IMRT plan has the average gamma pass rate of 94.3 %. During the period of performing this work a routine MLC calibration was performed and one of the IMRT treatments re-measured with the EPID. A change in the gamma pass rate for one field was observed. This was the motivation for a series of experiments to investigate the sensitivity of the method by introducing delivery errors, MLC position and dosimetric overshoot, into the simulated EPID images. The method was found to be sensitive to 1 mm leaf position errors and 10 % overshoot errors.

TU-F-BRF-06: 3D Pancreas MRI Segmentation Using Dictionary Learning and Manifold Clustering

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gou, S; Rapacchi, S; Hu, P

2014-06-15

Purpose: The recent advent of MRI guided radiotherapy machines has lent an exciting platform for soft tissue target localization during treatment. However, tools to efficiently utilize MRI images for such purpose have not been developed. Specifically, to efficiently quantify the organ motion, we develop an automated segmentation method using dictionary learning and manifold clustering (DLMC). Methods: Fast 3D HASTE and VIBE MR images of 2 healthy volunteers and 3 patients were acquired. A bounding box was defined to include pancreas and surrounding normal organs including the liver, duodenum and stomach. The first slice of the MRI was used for dictionarymore » learning based on mean-shift clustering and K-SVD sparse representation. Subsequent images were iteratively reconstructed until the error is less than a preset threshold. The preliminarily segmentation was subject to the constraints of manifold clustering. The segmentation results were compared with the mean shift merging (MSM), level set (LS) and manual segmentation methods. Results: DLMC resulted in consistently higher accuracy and robustness than comparing methods. Using manual contours as the ground truth, the mean Dices indices for all subjects are 0.54, 0.56 and 0.67 for MSM, LS and DLMC, respectively based on the HASTE image. The mean Dices indices are 0.70, 0.77 and 0.79 for the three methods based on VIBE images. DLMC is clearly more robust on the patients with the diseased pancreas while LS and MSM tend to over-segment the pancreas. DLMC also achieved higher sensitivity (0.80) and specificity (0.99) combining both imaging techniques. LS achieved equivalent sensitivity on VIBE images but was more computationally inefficient. Conclusion: We showed that pancreas and surrounding normal organs can be reliably segmented based on fast MRI using DLMC. This method will facilitate both planning volume definition and imaging guidance during treatment.« less

Rapid Assessment of Contrast Sensitivity with Mobile Touch-screens

NASA Technical Reports Server (NTRS)

Mulligan, Jeffrey B.

2013-01-01

The availability of low-cost high-quality touch-screen displays in modern mobile devices has created opportunities for new approaches to routine visual measurements. Here we describe a novel method in which subjects use a finger swipe to indicate the transition from visible to invisible on a grating which is swept in both contrast and frequency. Because a single image can be swiped in about a second, it is practical to use a series of images to zoom in on particular ranges of contrast or frequency, both to increase the accuracy of the measurements and to obtain an estimate of the reliability of the subject. Sensitivities to chromatic and spatio-temporal modulations are easily measured using the same method. We will demonstrate a prototype for Apple Computer's iPad-iPod-iPhone family of devices, implemented using an open-source scripting environment known as QuIP (QUick Image Processing,

Recognition algorithm for assisting ovarian cancer diagnosis from coregistered ultrasound and photoacoustic images: ex vivo study

NASA Astrophysics Data System (ADS)

Alqasemi, Umar; Kumavor, Patrick; Aguirre, Andres; Zhu, Quing

2012-12-01

Unique features and the underlining hypotheses of how these features may relate to the tumor physiology in coregistered ultrasound and photoacoustic images of ex vivo ovarian tissue are introduced. The images were first compressed with wavelet transform. The mean Radon transform of photoacoustic images was then computed and fitted with a Gaussian function to find the centroid of a suspicious area for shift-invariant recognition process. Twenty-four features were extracted from a training set by several methods, including Fourier transform, image statistics, and different composite filters. The features were chosen from more than 400 training images obtained from 33 ex vivo ovaries of 24 patients, and used to train three classifiers, including generalized linear model, neural network, and support vector machine (SVM). The SVM achieved the best training performance and was able to exclusively separate cancerous from non-cancerous cases with 100% sensitivity and specificity. At the end, the classifiers were used to test 95 new images obtained from 37 ovaries of 20 additional patients. The SVM classifier achieved 76.92% sensitivity and 95.12% specificity. Furthermore, if we assume that recognizing one image as a cancer is sufficient to consider an ovary as malignant, the SVM classifier achieves 100% sensitivity and 87.88% specificity.

A fuzzy feature fusion method for auto-segmentation of gliomas with multi-modality diffusion and perfusion magnetic resonance images in radiotherapy.

PubMed

Guo, Lu; Wang, Ping; Sun, Ranran; Yang, Chengwen; Zhang, Ning; Guo, Yu; Feng, Yuanming

2018-02-19

The diffusion and perfusion magnetic resonance (MR) images can provide functional information about tumour and enable more sensitive detection of the tumour extent. We aimed to develop a fuzzy feature fusion method for auto-segmentation of gliomas in radiotherapy planning using multi-parametric functional MR images including apparent diffusion coefficient (ADC), fractional anisotropy (FA) and relative cerebral blood volume (rCBV). For each functional modality, one histogram-based fuzzy model was created to transform image volume into a fuzzy feature space. Based on the fuzzy fusion result of the three fuzzy feature spaces, regions with high possibility belonging to tumour were generated automatically. The auto-segmentations of tumour in structural MR images were added in final auto-segmented gross tumour volume (GTV). For evaluation, one radiation oncologist delineated GTVs for nine patients with all modalities. Comparisons between manually delineated and auto-segmented GTVs showed that, the mean volume difference was 8.69% (±5.62%); the mean Dice's similarity coefficient (DSC) was 0.88 (±0.02); the mean sensitivity and specificity of auto-segmentation was 0.87 (±0.04) and 0.98 (±0.01) respectively. High accuracy and efficiency can be achieved with the new method, which shows potential of utilizing functional multi-parametric MR images for target definition in precision radiation treatment planning for patients with gliomas.

An Image Encryption Algorithm Utilizing Julia Sets and Hilbert Curves

PubMed Central

Sun, Yuanyuan; Chen, Lina; Xu, Rudan; Kong, Ruiqing

2014-01-01

Image encryption is an important and effective technique to protect image security. In this paper, a novel image encryption algorithm combining Julia sets and Hilbert curves is proposed. The algorithm utilizes Julia sets’ parameters to generate a random sequence as the initial keys and gets the final encryption keys by scrambling the initial keys through the Hilbert curve. The final cipher image is obtained by modulo arithmetic and diffuse operation. In this method, it needs only a few parameters for the key generation, which greatly reduces the storage space. Moreover, because of the Julia sets’ properties, such as infiniteness and chaotic characteristics, the keys have high sensitivity even to a tiny perturbation. The experimental results indicate that the algorithm has large key space, good statistical property, high sensitivity for the keys, and effective resistance to the chosen-plaintext attack. PMID:24404181

Near-infrared imaging for management of chronic maxillary sinusitis

NASA Astrophysics Data System (ADS)

You, Joon S.; Cerussi, Albert E.; Kim, James; Ison, Sean; Wong, Brian; Cui, Haotian; Bhandarkar, Naveen

2015-03-01

Efficient management of chronic sinusitis remains a great challenge for primary care physicians. Unlike ENT specialists using Computed Tomography scans, they lack an affordable and safe method to accurately screen and monitor sinus diseases in primary care settings. Lack of evidence-based sinusitis management leads to frequent under-treatments and unnecessary over-treatments (i.e. antibiotics). Previously, we reported low-cost optical imaging designs for oral illumination and facial optical imaging setup. It exploits the sensitivity of NIR transmission intensity and their unique patterns to the sinus structures and presence of fluid/mucous-buildup within the sinus cavities. Using the improved NIR system, we have obtained NIR sinus images of 45 subjects with varying degrees of sinusitis symptoms. We made diagnoses of these patients based on two types of evidence: symptoms alone or NIR images along. These diagnostic results were then compared to the gold standard diagnosis using computed tomography through sensitivity and specificity analysis. Our results indicate that diagnosis of mere presence of sinusitis that is, distinguishing between healthy individuals vs. diseased individuals did not improve much when using NIR imaging compared to the diagnosis based on symptoms alone (69% in sensitivity, 75% specificity). However, use of NIR imaging improved the differential diagnosis between mild and severe diseases significantly as the sensitivity improved from 75% for using diagnosis based on symptoms alone up to 95% for using diagnosis based on NIR images. Reported results demonstrate great promise for using NIR imaging system for management of chronic sinusitis patients in primary care settings without resorting to CT.

Diagnostic imaging and interventional therapy of hepatocellular carcinoma.

PubMed

Palma, L D

1998-08-01

Diagnostic imaging has many important roles in the management of patients with hepatocellular carcinoma (HCC). In diagnosis, lipiodol CT (LCT) has been shown to be the most sensitive imaging modality (90-97%) for all sizes of lesions; all other modalities have high sensitivities for lesions 1-3 cm but low sensitivities for lesions < 1 cm (ultrasound 33-37%, conventional CT 20-42% and digital subtraction angiography 40-55%). All imaging modalities understage HCC. Once again LCT is the most accurate method of evaluating the extent of tumour, but even this method does not identify all satellite nodules. Ultrasound has been proposed as a screening method, but this cannot be justified on the basis of its results or cost benefit analysis. Both CT and dynamic MRI play useful roles in evaluating the efficacy and follow-up of patients undergoing chemoembolization (TACE) and percutaneous ethanol injection (PEI). Although surgery remains the best treatment of HCC, it is unsuitable in most of the cases which would be better treated with interventional therapy. This article presents a review of the literature regarding the use of TACE, PEI or a combination of both procedures in the treatment of HCC. A multicentric study has shown that patients with monofocal lesions less than 5 cm in diameter are better treated with PEI, which is therefore a good alternative to the surgical treatment; patients with multifocal lesions (maximum of three lesions) show a better survival with TACE. Combined treatment with TACE and PEI proves to be effective in patients with large HCC.

Measurement Consistency from Magnetic Resonance Images

PubMed Central

Chung, Dongjun; Chung, Moo K.; Durtschi, Reid B.; Lindell, R. Gentry; Vorperian, Houri K.

2010-01-01

Rationale and Objectives In quantifying medical images, length-based measurements are still obtained manually. Due to possible human error, a measurement protocol is required to guarantee the consistency of measurements. In this paper, we review various statistical techniques that can be used in determining measurement consistency. The focus is on detecting a possible measurement bias and determining the robustness of the procedures to outliers. Materials and Methods We review correlation analysis, linear regression, Bland-Altman method, paired t-test, and analysis of variance (ANOVA). These techniques were applied to measurements, obtained by two raters, of head and neck structures from magnetic resonance images (MRI). Results The correlation analysis and the linear regression were shown to be insufficient for detecting measurement inconsistency. They are also very sensitive to outliers. The widely used Bland-Altman method is a visualization technique so it lacks the numerical quantification. The paired t-test tends to be sensitive to small measurement bias. On the other hand, ANOVA performs well even under small measurement bias. Conclusion In almost all cases, using only one method is insufficient and it is recommended to use several methods simultaneously. In general, ANOVA performs the best. PMID:18790405

Recognizing ovarian cancer from co-registered ultrasound and photoacoustic images

NASA Astrophysics Data System (ADS)

Alqasemi, Umar; Kumavor, Patrick; Aguirre, Andres; Zhu, Quing

2013-03-01

Unique features in co-registered ultrasound and photoacoustic images of ex vivo ovarian tissue are introduced, along with the hypotheses of how these features may relate to the physiology of tumors. The images are compressed with wavelet transform, after which the mean Radon transform of the photoacoustic image is computed and fitted with a Gaussian function to find the centroid of the suspicious area for shift-invariant recognition process. In the next step, 24 features are extracted from a training set of images by several methods; including features from the Fourier domain, image statistics, and the outputs of different composite filters constructed from the joint frequency response of different cancerous images. The features were chosen from more than 400 training images obtained from 33 ex vivo ovaries of 24 patients, and used to train a support vector machine (SVM) structure. The SVM classifier was able to exclusively separate the cancerous from the non-cancerous cases with 100% sensitivity and specificity. At the end, the classifier was used to test 95 new images, obtained from 37 ovaries of 20 additional patients. The SVM classifier achieved 76.92% sensitivity and 95.12% specificity. Furthermore, if we assume that recognizing one image as a cancerous case is sufficient to consider the ovary as malignant, then the SVM classifier achieves 100% sensitivity and 87.88% specificity.

Classification of CT examinations for COPD visual severity analysis

NASA Astrophysics Data System (ADS)

Tan, Jun; Zheng, Bin; Wang, Xingwei; Pu, Jiantao; Gur, David; Sciurba, Frank C.; Leader, J. Ken

2012-03-01

In this study we present a computational method of CT examination classification into visual assessed emphysema severity. The visual severity categories ranged from 0 to 5 and were rated by an experienced radiologist. The six categories were none, trace, mild, moderate, severe and very severe. Lung segmentation was performed for every input image and all image features are extracted from the segmented lung only. We adopted a two-level feature representation method for the classification. Five gray level distribution statistics, six gray level co-occurrence matrix (GLCM), and eleven gray level run-length (GLRL) features were computed for each CT image depicted segment lung. Then we used wavelets decomposition to obtain the low- and high-frequency components of the input image, and again extract from the lung region six GLCM features and eleven GLRL features. Therefore our feature vector length is 56. The CT examinations were classified using the support vector machine (SVM) and k-nearest neighbors (KNN) and the traditional threshold (density mask) approach. The SVM classifier had the highest classification performance of all the methods with an overall sensitivity of 54.4% and a 69.6% sensitivity to discriminate "no" and "trace visually assessed emphysema. We believe this work may lead to an automated, objective method to categorically classify emphysema severity on CT exam.

Differential diagnosis of neurodegenerative diseases using structural MRI data

PubMed Central

Koikkalainen, Juha; Rhodius-Meester, Hanneke; Tolonen, Antti; Barkhof, Frederik; Tijms, Betty; Lemstra, Afina W.; Tong, Tong; Guerrero, Ricardo; Schuh, Andreas; Ledig, Christian; Rueckert, Daniel; Soininen, Hilkka; Remes, Anne M.; Waldemar, Gunhild; Hasselbalch, Steen; Mecocci, Patrizia; van der Flier, Wiesje; Lötjönen, Jyrki

2016-01-01

Different neurodegenerative diseases can cause memory disorders and other cognitive impairments. The early detection and the stratification of patients according to the underlying disease are essential for an efficient approach to this healthcare challenge. This emphasizes the importance of differential diagnostics. Most studies compare patients and controls, or Alzheimer's disease with one other type of dementia. Such a bilateral comparison does not resemble clinical practice, where a clinician is faced with a number of different possible types of dementia. Here we studied which features in structural magnetic resonance imaging (MRI) scans could best distinguish four types of dementia, Alzheimer's disease, frontotemporal dementia, vascular dementia, and dementia with Lewy bodies, and control subjects. We extracted an extensive set of features quantifying volumetric and morphometric characteristics from T1 images, and vascular characteristics from FLAIR images. Classification was performed using a multi-class classifier based on Disease State Index methodology. The classifier provided continuous probability indices for each disease to support clinical decision making. A dataset of 504 individuals was used for evaluation. The cross-validated classification accuracy was 70.6% and balanced accuracy was 69.1% for the five disease groups using only automatically determined MRI features. Vascular dementia patients could be detected with high sensitivity (96%) using features from FLAIR images. Controls (sensitivity 82%) and Alzheimer's disease patients (sensitivity 74%) could be accurately classified using T1-based features, whereas the most difficult group was the dementia with Lewy bodies (sensitivity 32%). These results were notable better than the classification accuracies obtained with visual MRI ratings (accuracy 44.6%, balanced accuracy 51.6%). Different quantification methods provided complementary information, and consequently, the best results were obtained by utilizing several quantification methods. The results prove that automatic quantification methods and computerized decision support methods are feasible for clinical practice and provide comprehensive information that may help clinicians in the diagnosis making. PMID:27104138

Monte Carlo simulations of GeoPET experiments: 3D images of tracer distributions (18F, 124I and 58Co) in Opalinus clay, anhydrite and quartz

NASA Astrophysics Data System (ADS)

Zakhnini, Abdelhamid; Kulenkampff, Johannes; Sauerzapf, Sophie; Pietrzyk, Uwe; Lippmann-Pipke, Johanna

2013-08-01

Understanding conservative fluid flow and reactive tracer transport in soils and rock formations requires quantitative transport visualization methods in 3D+t. After a decade of research and development we established the GeoPET as a non-destructive method with unrivalled sensitivity and selectivity, with due spatial and temporal resolution by applying Positron Emission Tomography (PET), a nuclear medicine imaging method, to dense rock material. Requirements for reaching the physical limit of image resolution of nearly 1 mm are (a) a high-resolution PET-camera, like our ClearPET scanner (Raytest), and (b) appropriate correction methods for scatter and attenuation of 511 keV—photons in the dense geological material. The latter are by far more significant in dense geological material than in human and small animal body tissue (water). Here we present data from Monte Carlo simulations (MCS) reflecting selected GeoPET experiments. The MCS consider all involved nuclear physical processes of the measurement with the ClearPET-system and allow us to quantify the sensitivity of the method and the scatter fractions in geological media as function of material (quartz, Opalinus clay and anhydrite compared to water), PET isotope (18F, 58Co and 124I), and geometric system parameters. The synthetic data sets obtained by MCS are the basis for detailed performance assessment studies allowing for image quality improvements. A scatter correction method is applied exemplarily by subtracting projections of simulated scattered coincidences from experimental data sets prior to image reconstruction with an iterative reconstruction process.

Non-invasive dynamic near-infrared imaging and quantification of vascular leakage in vivo.

PubMed

Proulx, Steven T; Luciani, Paola; Alitalo, Annamari; Mumprecht, Viviane; Christiansen, Ailsa J; Huggenberger, Reto; Leroux, Jean-Christophe; Detmar, Michael

2013-07-01

Preclinical vascular research has been hindered by a lack of methods that can sensitively image and quantify vascular perfusion and leakage in vivo. In this study, we have developed dynamic near-infrared imaging methods to repeatedly visualize and quantify vascular leakage in mouse skin in vivo, and we have applied these methods to transgenic mice with overexpression of vascular endothelial growth factors VEGF-A or -C. Near-infrared dye conjugates were developed to identify a suitable vascular tracer that had a prolonged circulation lifetime and slow leakage into normal tissue after intravenous injection. Dynamic simultaneous imaging of ear skin and a large blood vessel in the leg enabled determination of the intravascular signal (blood volume fraction) from the tissue signal shortly after injection and quantifications of vascular leakage into the extravascular tissue over time. This method allowed for the sensitive detection of increased blood vascularity and leakage rates in K14-VEGF-A transgenic mice and also reliably measured inflammation-induced changes of vascularity and leakage over time in the same mice. Measurements after injection of recombinant VEGF-A surprisingly revealed increased blood vascular leakage and lymphatic clearance in K14-VEGF-C transgenic mice which have an expanded cutaneous lymphatic vessel network, potentially indicating unanticipated effects of lymphatic drainage on vascular leakage. Increased vascular leakage was also detected in subcutaneous tumors, confirming that the method can also be applied to deeper tissues. This new imaging method might facilitate longitudinal investigations of the in vivo effects of drug candidates, including angiogenesis inhibitors, in preclinical disease models.

Non-invasive dynamic near-infrared imaging and quantification of vascular leakage in vivo

PubMed Central

Proulx, Steven T.; Luciani, Paola; Alitalo, Annamari; Mumprecht, Viviane; Christiansen, Ailsa J.; Huggenberger, Reto

2013-01-01

Preclinical vascular research has been hindered by a lack of methods that can sensitively image and quantify vascular perfusion and leakage in vivo. In this study, we have developed dynamic near-infrared imaging methods to repeatedly visualize and quantify vascular leakage in mouse skin in vivo, and we have applied these methods to transgenic mice with overexpression of vascular endothelial growth factors VEGF-A or -C. Near-infrared dye conjugates were developed to identify a suitable vascular tracer that had a prolonged circulation lifetime and slow leakage into normal tissue after intravenous injection. Dynamic simultaneous imaging of ear skin and a large blood vessel in the leg enabled determination of the intravascular signal (blood volume fraction) from the tissue signal shortly after injection and quantifications of vascular leakage into the extravascular tissue over time. This method allowed for the sensitive detection of increased blood vascularity and leakage rates in K14-VEGF-A transgenic mice and also reliably measured inflammation-induced changes of vascularity and leakage over time in the same mice. Measurements after injection of recombinant VEGF-A surprisingly revealed increased blood vascular leakage and lymphatic clearance in K14-VEGF-C transgenic mice which have an expanded cutaneous lymphatic vessel network, potentially indicating unanticipated effects of lymphatic drainage on vascular leakage. Increased vascular leakage was also detected in subcutaneous tumors, confirming that the method can also be applied to deeper tissues. This new imaging method might facilitate longitudinal investigations of the in vivo effects of drug candidates, including angiogenesis inhibitors, in preclinical disease models. PMID:23325334

Towards a high sensitivity small animal PET system based on CZT detectors (Conference Presentation)

NASA Astrophysics Data System (ADS)

Abbaszadeh, Shiva; Levin, Craig

2017-03-01

Small animal positron emission tomography (PET) is a biological imaging technology that allows non-invasive interrogation of internal molecular and cellular processes and mechanisms of disease. New PET molecular probes with high specificity are under development to target, detect, visualize, and quantify subtle molecular and cellular processes associated with cancer, heart disease, and neurological disorders. However, the limited uptake of these targeted probes leads to significant reduction in signal. There is a need to advance the performance of small animal PET system technology to reach its full potential for molecular imaging. Our goal is to assemble a small animal PET system based on CZT detectors and to explore methods to enhance its photon sensitivity. In this work, we reconstruct an image from a phantom using a two-panel subsystem consisting of six CZT crystals in each panel. For image reconstruction, coincidence events with energy between 450 and 570 keV were included. We are developing an algorithm to improve sensitivity of the system by including multiple interaction events.

Diagnostic Accuracy of Preoperative Gadoxetic Acid–enhanced 3-T MR Imaging for Malignant Liver Lesions by Using Ex Vivo MR Imaging–matched Pathologic Findings as the Reference Standard1

PubMed Central

Costa, Eduardo A. C.; Cunha, Guilherme M.; Smorodinsky, Emmanuil; Cruite, Irene; Tang, An; Marks, Robert M.; Clark, Lisa; Wolfson, Tanya; Gamst, Anthony; Sicklick, Jason K.; Hemming, Alan; Peterson, Michael R.; Middleton, Michael S.; Sirlin, Claude B.

2016-01-01

Purpose To determine per-lesion sensitivity and positive predictive value (PPV) of gadoxetic acid–enhanced 3-T magnetic resonance (MR) imaging for the diagnosis of malignant lesions by using matched (spatially correlated) hepatectomy pathologic findings as the reference standard. Materials and Methods In this prospective, institutional review board–approved, HIPAA-compliant study, 20 patients (nine men, 11 women; mean age, 59 years) with malignant liver lesions who gave written informed consent underwent preoperative gadoxetic acid–enhanced 3-T MR imaging for surgical planning. Two image sets were independently analyzed by three readers to detect liver lesions (set 1 without and set 2 with hepatobiliary phase [HBP] images). Hepatectomy specimen ex vivo MR imaging assisted in matching gadoxetic acid–enhanced 3-T MR imaging findings with pathologic findings. Interreader agreement was assessed by using the Cohen k coefficient. Per-lesion sensitivity and PPV were calculated. Results Cohen k values were 0.64–0.76 and 0.57–0.84, and overall per-lesion sensitivity was 45% (42 of 94 lesions) to 56% (53 of 94 lesions) and 58% (55 of 94 lesions) to 64% (60 of 94 lesions) for sets 1 and 2, respectively. The addition of HBP imaging did not affect interreader agreement but significantly improved overall sensitivity for one reader (P < .05) and almost for another (P = .05). Sensitivity for 0.2–0.5-cm lesions was 0% (0 of 26 lesions) to 8% (two of 26 lesions) for set 1 and 4% (one of 26 lesions) to 12% (three of 26 lesions) for set 2. Sensitivity for 0.6–1.0-cm lesions was 28% (nine of 32 lesions) to 59% (19 of 32 lesions) for set 1 and 66% (21 of 32 lesions) to 69% (22 of 32 lesions) for set 2. Sensitivity for lesions at least 1.0 cm in diameter was at least 81% (13 of 16 lesions) for set 1 and was not improved for set 2. PPV was 98% (56 of 57 lesions) to 100% (60 of 60 lesions) for all readers without differences between image sets or lesion size. Conclusion Gadoxetic acid–enhanced 3-T MR imaging provides high per-lesion sensitivity and PPV for preoperative malignant liver lesion detection overall, although sensitivity for 0.2–0.5-cm malignant lesions is poor. PMID:25875972

SU-C-201-04: Quantification of Perfusion Heterogeneity Based On Texture Analysis for Fully Automatic Detection of Ischemic Deficits From Myocardial Perfusion Imaging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fang, Y; Huang, H; Su, T

Purpose: Texture-based quantification of image heterogeneity has been a popular topic for imaging studies in recent years. As previous studies mainly focus on oncological applications, we report our recent efforts of applying such techniques on cardiac perfusion imaging. A fully automated procedure has been developed to perform texture analysis for measuring the image heterogeneity. Clinical data were used to evaluate the preliminary performance of such methods. Methods: Myocardial perfusion images of Thallium-201 scans were collected from 293 patients with suspected coronary artery disease. Each subject underwent a Tl-201 scan and a percutaneous coronary intervention (PCI) within three months. The PCImore » Result was used as the gold standard of coronary ischemia of more than 70% stenosis. Each Tl-201 scan was spatially normalized to an image template for fully automatic segmentation of the LV. The segmented voxel intensities were then carried into the texture analysis with our open-source software Chang Gung Image Texture Analysis toolbox (CGITA). To evaluate the clinical performance of the image heterogeneity for detecting the coronary stenosis, receiver operating characteristic (ROC) analysis was used to compute the overall accuracy, sensitivity and specificity as well as the area under curve (AUC). Those indices were compared to those obtained from the commercially available semi-automatic software QPS. Results: With the fully automatic procedure to quantify heterogeneity from Tl-201 scans, we were able to achieve a good discrimination with good accuracy (74%), sensitivity (73%), specificity (77%) and AUC of 0.82. Such performance is similar to those obtained from the semi-automatic QPS software that gives a sensitivity of 71% and specificity of 77%. Conclusion: Based on fully automatic procedures of data processing, our preliminary data indicate that the image heterogeneity of myocardial perfusion imaging can provide useful information for automatic determination of the myocardial ischemia.« less

Dependence of image quality on image operator and noise for optical diffusion tomography

NASA Astrophysics Data System (ADS)

Chang, Jenghwa; Graber, Harry L.; Barbour, Randall L.

1998-04-01

By applying linear perturbation theory to the radiation transport equation, the inverse problem of optical diffusion tomography can be reduced to a set of linear equations, W(mu) equals R, where W is the weight function, (mu) are the cross- section perturbations to be imaged, and R is the detector readings perturbations. We have studied the dependence of image quality on added systematic error and/or random noise in W and R. Tomographic data were collected from cylindrical phantoms, with and without added inclusions, using Monte Carlo methods. Image reconstruction was accomplished using a constrained conjugate gradient descent method. Result show that accurate images containing few artifacts are obtained when W is derived from a reference states whose optical thickness matches that of the unknown teste medium. Comparable image quality was also obtained for unmatched W, but the location of the target becomes more inaccurate as the mismatch increases. Results of the noise study show that image quality is much more sensitive to noise in W than in R, and the impact of noise increase with the number of iterations. Images reconstructed after pure noise was substituted for R consistently contain large peaks clustered about the cylinder axis, which was an initially unexpected structure. In other words, random input produces a non- random output. This finding suggests that algorithms sensitive to the evolution of this feature could be developed to suppress noise effects.

Cross Correlation versus Normalized Mutual Information on Image Registration

NASA Technical Reports Server (NTRS)

Tan, Bin; Tilton, James C.; Lin, Guoqing

2016-01-01

This is the first study to quantitatively assess and compare cross correlation and normalized mutual information methods used to register images in subpixel scale. The study shows that the normalized mutual information method is less sensitive to unaligned edges due to the spectral response differences than is cross correlation. This characteristic makes the normalized image resolution a better candidate for band to band registration. Improved band-to-band registration in the data from satellite-borne instruments will result in improved retrievals of key science measurements such as cloud properties, vegetation, snow and fire.

High-sensitivity detection of breast tumors in vivo by use of a pH-sensitive near-infrared fluorescence probe

NASA Astrophysics Data System (ADS)

Mathejczyk, Julia Eva; Pauli, Jutta; Dullin, Christian; Resch-Genger, Ute; Alves, Frauke; Napp, Joanna

2012-07-01

We investigated the potential of the pH-sensitive dye, CypHer5E, conjugated to Herceptin (pH-Her) for the sensitive detection of breast tumors in mice using noninvasive time-domain near-infrared fluorescence imaging and different methods of data analysis. First, the fluorescence properties of pH-Her were analyzed as function of pH and/or dye-to-protein ratio, and binding specificity was confirmed in cell-based assays. Subsequently, the performance of pH-Her in nude mice bearing orthotopic HER2-positive (KPL-4) and HER2-negative (MDA-MB-231) breast carcinoma xenografts was compared to that of an always-on fluorescent conjugate Alexa Fluor 647-Herceptin (Alexa-Her). Subtraction of autofluorescence and lifetime (LT)-gated image analyses were performed for background fluorescence suppression. In mice bearing HER2-positive tumors, autofluorescence subtraction together with the selective fluorescence enhancement of pH-Her solely in the tumor's acidic environment provided high contrast-to-noise ratios (CNRs). This led to an improved sensitivity of tumor detection compared to Alexa-Her. In contrast, LT-gated imaging using LTs determined in model systems did not improve tumor-detection sensitivity in vivo for either probe. In conclusion, pH-Her is suitable for sensitive in vivo monitoring of HER2-expressing breast tumors with imaging in the intensity domain and represents a promising tool for detection of weak fluorescent signals deriving from small tumors or metastases.

Three-dimensional ghost imaging lidar via sparsity constraint

NASA Astrophysics Data System (ADS)

Gong, Wenlin; Zhao, Chengqiang; Yu, Hong; Chen, Mingliang; Xu, Wendong; Han, Shensheng

2016-05-01

Three-dimensional (3D) remote imaging attracts increasing attentions in capturing a target’s characteristics. Although great progress for 3D remote imaging has been made with methods such as scanning imaging lidar and pulsed floodlight-illumination imaging lidar, either the detection range or application mode are limited by present methods. Ghost imaging via sparsity constraint (GISC), enables the reconstruction of a two-dimensional N-pixel image from much fewer than N measurements. By GISC technique and the depth information of targets captured with time-resolved measurements, we report a 3D GISC lidar system and experimentally show that a 3D scene at about 1.0 km range can be stably reconstructed with global measurements even below the Nyquist limit. Compared with existing 3D optical imaging methods, 3D GISC has the capability of both high efficiency in information extraction and high sensitivity in detection. This approach can be generalized in nonvisible wavebands and applied to other 3D imaging areas.

Near-infrared imaging of water in human hair.

PubMed

Egawa, Mariko; Hagihara, Motofumi; Yanai, Motohiro

2013-02-01

The water content of hair can be evaluated by weighing, the Karl Fischer method, and from electrical properties. However, these methods cannot be used to study the distribution of water in the hair. Imaging techniques are required for this purpose. In this study, a highly sensitive near-infrared (NIR) imaging system was developed for evaluating water in human hair. The results obtained from NIR imaging and conventional methods were compared. An extended indium-gallium-arsenide NIR camera (detection range: 1100-2200 nm) and diffuse illumination unit developed in our laboratory were used to obtain a NIR image of hair. A water image was obtained using a 1950-nm interference filter and polarization filter. Changes in the hair water content with relative humidity (20-95% RH) and after immersion in a 7% (w/w) sorbitol solution were measured using the NIR camera and an insulation resistance tester. The changes in the water content after treatment with two types of commercially available shampoo were also measured using the NIR camera. As the water content increased with changes in the relative humidity, the brightness of the water image decreased and the insulation resistance decreased. The brightness in the NIR image of hair treated with sorbitol solution was lower than that in the image of hair treated with water. This shows the sorbitol-treated hair contains more water than water-treated hair. The sorbitol-treated hair had a lower resistance after treatment than before, which also shows that sorbitol treatment increases the water content. With this system, we could detect a difference in the moisturizing effect between two commercially available shampoos. The highly sensitive imaging system could be used to study water in human hair. Changes in the water content of hair depended on the relative humidity and treatment with moisturizer. The results obtained using the NIR imaging system were similar to those obtained using a conventional method. Our system could detect differences in the moisturizing effects of two commercially available shampoos. © 2012 John Wiley & Sons A/S.

Improvement of automatic hemorrhage detection methods using brightness correction on fundus images

NASA Astrophysics Data System (ADS)

Hatanaka, Yuji; Nakagawa, Toshiaki; Hayashi, Yoshinori; Kakogawa, Masakatsu; Sawada, Akira; Kawase, Kazuhide; Hara, Takeshi; Fujita, Hiroshi

2008-03-01

We have been developing several automated methods for detecting abnormalities in fundus images. The purpose of this study is to improve our automated hemorrhage detection method to help diagnose diabetic retinopathy. We propose a new method for preprocessing and false positive elimination in the present study. The brightness of the fundus image was changed by the nonlinear curve with brightness values of the hue saturation value (HSV) space. In order to emphasize brown regions, gamma correction was performed on each red, green, and blue-bit image. Subsequently, the histograms of each red, blue, and blue-bit image were extended. After that, the hemorrhage candidates were detected. The brown regions indicated hemorrhages and blood vessels and their candidates were detected using density analysis. We removed the large candidates such as blood vessels. Finally, false positives were removed by using a 45-feature analysis. To evaluate the new method for the detection of hemorrhages, we examined 125 fundus images, including 35 images with hemorrhages and 90 normal images. The sensitivity and specificity for the detection of abnormal cases was were 80% and 88%, respectively. These results indicate that the new method may effectively improve the performance of our computer-aided diagnosis system for hemorrhages.

Optimized lighting method of applying shaped-function signal for increasing the dynamic range of LED-multispectral imaging system

NASA Astrophysics Data System (ADS)

Yang, Xue; Hu, Yajia; Li, Gang; Lin, Ling

2018-02-01

This paper proposes an optimized lighting method of applying a shaped-function signal for increasing the dynamic range of light emitting diode (LED)-multispectral imaging system. The optimized lighting method is based on the linear response zone of the analog-to-digital conversion (ADC) and the spectral response of the camera. The auxiliary light at a higher sensitivity-camera area is introduced to increase the A/D quantization levels that are within the linear response zone of ADC and improve the signal-to-noise ratio. The active light is modulated by the shaped-function signal to improve the gray-scale resolution of the image. And the auxiliary light is modulated by the constant intensity signal, which is easy to acquire the images under the active light irradiation. The least square method is employed to precisely extract the desired images. One wavelength in multispectral imaging based on LED illumination was taken as an example. It has been proven by experiments that the gray-scale resolution and the accuracy of information of the images acquired by the proposed method were both significantly improved. The optimum method opens up avenues for the hyperspectral imaging of biological tissue.

Optimized lighting method of applying shaped-function signal for increasing the dynamic range of LED-multispectral imaging system.

PubMed

Yang, Xue; Hu, Yajia; Li, Gang; Lin, Ling

2018-02-01

This paper proposes an optimized lighting method of applying a shaped-function signal for increasing the dynamic range of light emitting diode (LED)-multispectral imaging system. The optimized lighting method is based on the linear response zone of the analog-to-digital conversion (ADC) and the spectral response of the camera. The auxiliary light at a higher sensitivity-camera area is introduced to increase the A/D quantization levels that are within the linear response zone of ADC and improve the signal-to-noise ratio. The active light is modulated by the shaped-function signal to improve the gray-scale resolution of the image. And the auxiliary light is modulated by the constant intensity signal, which is easy to acquire the images under the active light irradiation. The least square method is employed to precisely extract the desired images. One wavelength in multispectral imaging based on LED illumination was taken as an example. It has been proven by experiments that the gray-scale resolution and the accuracy of information of the images acquired by the proposed method were both significantly improved. The optimum method opens up avenues for the hyperspectral imaging of biological tissue.

The value of digital imaging in diabetic retinopathy.

PubMed

Sharp, P F; Olson, J; Strachan, F; Hipwell, J; Ludbrook, A; O'Donnell, M; Wallace, S; Goatman, K; Grant, A; Waugh, N; McHardy, K; Forrester, J V

2003-01-01

To assess the performance of digital imaging, compared with other modalities, in screening for and monitoring the development of diabetic retinopathy. All imaging was acquired at a hospital assessment clinic. Subsequently, study optometrists examined the patients in their own premises. A subset of patients also had fluorescein angiography performed every 6 months. Research clinic at the hospital eye clinic and optometrists' own premises. Study comprised 103 patients who had type 1 diabetes mellitus, 481 had type 2 diabetes mellitus and two had secondary diabetes mellitus; 157 (26.8%) had some form of retinopathy ('any') and 58 (9.9%) had referable retinopathy. A repeat assessment was carried out of all patients 1 year after their initial assessment. Patients who had more severe forms of retinopathy were monitored more frequently for evidence of progression. Detection of retinopathy, progression of retinopathy and determination of when treatment is required. Manual grading of 35-mm colour slides produced the highest sensitivity and specificity figures, with optometrist examination recording most false negatives. Manual and automated analysis of digital images had intermediate sensitivity. Both manual grading of 35-mm colour slides and digital images gave sensitivities of over 90% with few false positives. Digital imaging produced 50% fewer ungradable images than colour slides. This part of the study was limited as patients with the more severe levels of retinopathy opted for treatment. There was an increase in the number of microaneurysms in those patients who developed from mild to moderate. There was no difference between the turnover rate of either new or regressed microaneurysms for patients with mild or with sight-threatening retinopathy. It was not possible in this study to ascertain whether digital imaging systems determine when treatment is warranted. In the context of a national screening programme for referable retinopathy, digital imaging is an effective method. In addition, technical failure rates are lower with digital imaging than conventional photography. Digital imaging is also a more sensitive technique than slit-lamp examination by optometrists. Automated grading can improve efficiency by correctly identifying just under half the population as having no retinopathy. Recommendations for future research include: investigating whether the nasal field is required for grading; a large screening programme is required to ascertain if automated grading can safely perform as a first-level grader; if colour improves the performance of grading digital images; investigating methods to ensure effective uptake in a diabetic retinopathy screening programme.

Coherent imaging at the diffraction limit

PubMed Central

Thibault, Pierre; Guizar-Sicairos, Manuel; Menzel, Andreas

2014-01-01

X-ray ptychography, a scanning coherent diffractive imaging technique, holds promise for imaging with dose-limited resolution and sensitivity. If the foreseen increase of coherent flux by orders of magnitude can be matched by additional technological and analytical advances, ptychography may approach imaging speeds familiar from full-field methods while retaining its inherently quantitative nature and metrological versatility. Beyond promises of high throughput, spectroscopic applications in three dimensions become feasible, as do measurements of sample dynamics through time-resolved imaging or careful characterization of decoherence effects. PMID:25177990

Coherent imaging at the diffraction limit.

PubMed

Thibault, Pierre; Guizar-Sicairos, Manuel; Menzel, Andreas

2014-09-01

X-ray ptychography, a scanning coherent diffractive imaging technique, holds promise for imaging with dose-limited resolution and sensitivity. If the foreseen increase of coherent flux by orders of magnitude can be matched by additional technological and analytical advances, ptychography may approach imaging speeds familiar from full-field methods while retaining its inherently quantitative nature and metrological versatility. Beyond promises of high throughput, spectroscopic applications in three dimensions become feasible, as do measurements of sample dynamics through time-resolved imaging or careful characterization of decoherence effects.

Intraoperative imaging-guided cancer surgery: from current fluorescence molecular imaging methods to future multi-modality imaging technology.

PubMed

Chi, Chongwei; Du, Yang; Ye, Jinzuo; Kou, Deqiang; Qiu, Jingdan; Wang, Jiandong; Tian, Jie; Chen, Xiaoyuan

2014-01-01

Cancer is a major threat to human health. Diagnosis and treatment using precision medicine is expected to be an effective method for preventing the initiation and progression of cancer. Although anatomical and functional imaging techniques such as radiography, computed tomography (CT), magnetic resonance imaging (MRI) and positron emission tomography (PET) have played an important role for accurate preoperative diagnostics, for the most part these techniques cannot be applied intraoperatively. Optical molecular imaging is a promising technique that provides a high degree of sensitivity and specificity in tumor margin detection. Furthermore, existing clinical applications have proven that optical molecular imaging is a powerful intraoperative tool for guiding surgeons performing precision procedures, thus enabling radical resection and improved survival rates. However, detection depth limitation exists in optical molecular imaging methods and further breakthroughs from optical to multi-modality intraoperative imaging methods are needed to develop more extensive and comprehensive intraoperative applications. Here, we review the current intraoperative optical molecular imaging technologies, focusing on contrast agents and surgical navigation systems, and then discuss the future prospects of multi-modality imaging technology for intraoperative imaging-guided cancer surgery.

Intraoperative Imaging-Guided Cancer Surgery: From Current Fluorescence Molecular Imaging Methods to Future Multi-Modality Imaging Technology

PubMed Central

Chi, Chongwei; Du, Yang; Ye, Jinzuo; Kou, Deqiang; Qiu, Jingdan; Wang, Jiandong; Tian, Jie; Chen, Xiaoyuan

2014-01-01

Cancer is a major threat to human health. Diagnosis and treatment using precision medicine is expected to be an effective method for preventing the initiation and progression of cancer. Although anatomical and functional imaging techniques such as radiography, computed tomography (CT), magnetic resonance imaging (MRI) and positron emission tomography (PET) have played an important role for accurate preoperative diagnostics, for the most part these techniques cannot be applied intraoperatively. Optical molecular imaging is a promising technique that provides a high degree of sensitivity and specificity in tumor margin detection. Furthermore, existing clinical applications have proven that optical molecular imaging is a powerful intraoperative tool for guiding surgeons performing precision procedures, thus enabling radical resection and improved survival rates. However, detection depth limitation exists in optical molecular imaging methods and further breakthroughs from optical to multi-modality intraoperative imaging methods are needed to develop more extensive and comprehensive intraoperative applications. Here, we review the current intraoperative optical molecular imaging technologies, focusing on contrast agents and surgical navigation systems, and then discuss the future prospects of multi-modality imaging technology for intraoperative imaging-guided cancer surgery. PMID:25250092

Measurement of the ferric diffusion coefficient in agarose and gelatine gels by utilization of the evolution of a radiation induced edge as reflected in relaxation rate images.

PubMed

Pedersen, T V; Olsen, D R; Skretting, A

1997-08-01

A method has been developed to determine the diffusion coefficients of ferric ions in ferrous sulphate doped gels. A radiation induced edge was created in the gel, and two spin-echo sequences were used to acquire a pair of images of the gel at different points of time. For each of these image pairs, a longitudinal relaxation rate image was derived. From profiles through these images, the standard deviations of the Gaussian functions that characterize diffusion were determined. These data provided the basis for the determination of the ferric diffusion coefficients by two different methods. Simulations indicate that the use of single spin-echo images in this procedure may in some cases lead to a significant underestimation of the diffusion coefficient. The technique was applied to different agarose and gelatine gels that were prepared, irradiated and imaged simultaneously. The results indicate that the diffusion coefficient is lower in a gelatine gel than in an agarose gel. Addition of xylenol orange to a gelatine gel lowers the diffusion coefficient from 1.45 to 0.81 mm2 h-1, at the cost of significantly lower Rl sensitivity. The addition of benzoic acid to the latter gel did not increase the Rl sensitivity.

Dental MRI using wireless intraoral coils

NASA Astrophysics Data System (ADS)

Ludwig, Ute; Eisenbeiss, Anne-Katrin; Scheifele, Christian; Nelson, Katja; Bock, Michael; Hennig, Jürgen; von Elverfeldt, Dominik; Herdt, Olga; Flügge, Tabea; Hövener, Jan-Bernd

2016-03-01

Currently, the gold standard for dental imaging is projection radiography or cone-beam computed tomography (CBCT). These methods are fast and cost-efficient, but exhibit poor soft tissue contrast and expose the patient to ionizing radiation (X-rays). The need for an alternative imaging modality e.g. for soft tissue management has stimulated a rising interest in dental magnetic resonance imaging (MRI) which provides superior soft tissue contrast. Compared to X-ray imaging, however, so far the spatial resolution of MRI is lower and the scan time is longer. In this contribution, we describe wireless, inductively-coupled intraoral coils whose local sensitivity enables high resolution MRI of dental soft tissue. In comparison to CBCT, a similar image quality with complementary contrast was obtained ex vivo. In-vivo, a voxel size of the order of 250•250•500 μm3 was achieved in 4 min only. Compared to dental MRI acquired with clinical equipment, the quality of the images was superior in the sensitive volume of the coils and is expected to improve the planning of interventions and monitoring thereafter. This method may enable a more accurate dental diagnosis and avoid unnecessary interventions, improving patient welfare and bringing MRI a step closer to becoming a radiation-free alternative for dental imaging.

Effect of image quality on calcification detection in digital mammography.

PubMed

Warren, Lucy M; Mackenzie, Alistair; Cooke, Julie; Given-Wilson, Rosalind M; Wallis, Matthew G; Chakraborty, Dev P; Dance, David R; Bosmans, Hilde; Young, Kenneth C

2012-06-01

This study aims to investigate if microcalcification detection varies significantly when mammographic images are acquired using different image qualities, including: different detectors, dose levels, and different image processing algorithms. An additional aim was to determine how the standard European method of measuring image quality using threshold gold thickness measured with a CDMAM phantom and the associated limits in current EU guidelines relate to calcification detection. One hundred and sixty two normal breast images were acquired on an amorphous selenium direct digital (DR) system. Microcalcification clusters extracted from magnified images of slices of mastectomies were electronically inserted into half of the images. The calcification clusters had a subtle appearance. All images were adjusted using a validated mathematical method to simulate the appearance of images from a computed radiography (CR) imaging system at the same dose, from both systems at half this dose, and from the DR system at quarter this dose. The original 162 images were processed with both Hologic and Agfa (Musica-2) image processing. All other image qualities were processed with Agfa (Musica-2) image processing only. Seven experienced observers marked and rated any identified suspicious regions. Free response operating characteristic (FROC) and ROC analyses were performed on the data. The lesion sensitivity at a nonlesion localization fraction (NLF) of 0.1 was also calculated. Images of the CDMAM mammographic test phantom were acquired using the automatic setting on the DR system. These images were modified to the additional image qualities used in the observer study. The images were analyzed using automated software. In order to assess the relationship between threshold gold thickness and calcification detection a power law was fitted to the data. There was a significant reduction in calcification detection using CR compared with DR: the alternative FROC (AFROC) area decreased from 0.84 to 0.63 and the ROC area decreased from 0.91 to 0.79 (p < 0.0001). This corresponded to a 30% drop in lesion sensitivity at a NLF equal to 0.1. Detection was also sensitive to the dose used. There was no significant difference in detection between the two image processing algorithms used (p > 0.05). It was additionally found that lower threshold gold thickness from CDMAM analysis implied better cluster detection. The measured threshold gold thickness passed the acceptable limit set in the EU standards for all image qualities except half dose CR. However, calcification detection varied significantly between image qualities. This suggests that the current EU guidelines may need revising. Microcalcification detection was found to be sensitive to detector and dose used. Standard measurements of image quality were a good predictor of microcalcification cluster detection. © 2012 American Association of Physicists in Medicine.

75 FR 4569 - Government-Owned Inventions; Availability for Licensing

Federal Register 2010, 2011, 2012, 2013, 2014

2010-01-28

... [email protected] for more information. Imaging of Extracellular Proteases in Cells Using Mutant.... Fortunately, this is one of the least deadly cancers; the percentage of people living at least 5 years after... and sensitive methods for in vivo, in vitro, or ex vivo imaging of specific extracellular protease...

A Multimodal Imaging Protocol, (123)I/(99)Tc-Sestamibi, SPECT, and SPECT/CT, in Primary Hyperparathyroidism Adds Limited Benefit for Preoperative Localization.

PubMed

Lee, Grace S; McKenzie, Travis J; Mullan, Brian P; Farley, David R; Thompson, Geoffrey B; Richards, Melanie L

2016-03-01

Focused parathyroidectomy in primary hyperparathyroidism (1°HPT) is possible with accurate preoperative localization and intraoperative PTH monitoring (IOPTH). The added benefit of multimodal imaging techniques for operative success is unknown. Patients with 1°HPT, who underwent parathyroidectomy in 2012-2014 at a single institution, were retrospectively reviewed. Only the patients who underwent the standardized multimodal imaging workup consisting of (123)I/(99)Tc-sestamibi subtraction scintigraphy, SPECT, and SPECT/CT were assessed. Of 360 patients who were identified, a curative operation was performed in 96%, using pre-operative imaging and IOPTH. Imaging analysis showed that (123)I/(99)Tc-sestamibi had a sensitivity of 86% (95% CI 82-90%), positive predictive value (PPV) 93%, and accuracy 81%, based on correct lateralization. SPECT had a sensitivity of 77% (95% CI 72-82%), PPV 92% and accuracy 72%. SPECT/CT had a sensitivity of 75% (95% CI 70-80%), PPV of 94%, and accuracy 71%. There were 3 of 45 (7%) patients with negative sestamibi imaging that had an accurate SPECT and SPECT/CT. Of 312 patients (87%) with positive uptake on sestamibi (93% true positive, 7% false positive), concordant findings were present in 86% SPECT and 84% SPECT/CT. In cases where imaging modalities were discordant, but at least one method was true-positive, (123)I/(99)Tc-sestamibi was significantly better than both SPECT and SPECT/CT (p < 0.001). The inclusion of SPECT and SPECT/CT in 1°HPT imaging protocol increases patient cost up to 2.4-fold. (123)I/(99)Tc-sestamibi subtraction imaging is highly sensitive for preoperative localization in 1°HPT. SPECT and SPECT/CT are commonly concordant with (123)I/(99)Tc-sestamibi and rarely increase the sensitivity. Routine inclusion of multimodality imaging technique adds minimal clinical benefit but increases cost to patient in high-volume setting.

Calibrationless parallel magnetic resonance imaging: a joint sparsity model.

PubMed

Majumdar, Angshul; Chaudhury, Kunal Narayan; Ward, Rabab

2013-12-05

State-of-the-art parallel MRI techniques either explicitly or implicitly require certain parameters to be estimated, e.g., the sensitivity map for SENSE, SMASH and interpolation weights for GRAPPA, SPIRiT. Thus all these techniques are sensitive to the calibration (parameter estimation) stage. In this work, we have proposed a parallel MRI technique that does not require any calibration but yields reconstruction results that are at par with (or even better than) state-of-the-art methods in parallel MRI. Our proposed method required solving non-convex analysis and synthesis prior joint-sparsity problems. This work also derives the algorithms for solving them. Experimental validation was carried out on two datasets-eight channel brain and eight channel Shepp-Logan phantom. Two sampling methods were used-Variable Density Random sampling and non-Cartesian Radial sampling. For the brain data, acceleration factor of 4 was used and for the other an acceleration factor of 6 was used. The reconstruction results were quantitatively evaluated based on the Normalised Mean Squared Error between the reconstructed image and the originals. The qualitative evaluation was based on the actual reconstructed images. We compared our work with four state-of-the-art parallel imaging techniques; two calibrated methods-CS SENSE and l1SPIRiT and two calibration free techniques-Distributed CS and SAKE. Our method yields better reconstruction results than all of them.

Technical Note: Synchrotron-based high-energy x-ray phase sensitive microtomography for biomedical research

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Huiqiang; Wu, Xizeng, E-mail: xwu@uabmc.edu, E-mail: tqxiao@sinap.ac.cn; Xiao, Tiqiao, E-mail: xwu@uabmc.edu, E-mail: tqxiao@sinap.ac.cn

Purpose: Propagation-based phase-contrast CT (PPCT) utilizes highly sensitive phase-contrast technology applied to x-ray microtomography. Performing phase retrieval on the acquired angular projections can enhance image contrast and enable quantitative imaging. In this work, the authors demonstrate the validity and advantages of a novel technique for high-resolution PPCT by using the generalized phase-attenuation duality (PAD) method of phase retrieval. Methods: A high-resolution angular projection data set of a fish head specimen was acquired with a monochromatic 60-keV x-ray beam. In one approach, the projection data were directly used for tomographic reconstruction. In two other approaches, the projection data were preprocessed bymore » phase retrieval based on either the linearized PAD method or the generalized PAD method. The reconstructed images from all three approaches were then compared in terms of tissue contrast-to-noise ratio and spatial resolution. Results: The authors’ experimental results demonstrated the validity of the PPCT technique based on the generalized PAD-based method. In addition, the results show that the authors’ technique is superior to the direct PPCT technique as well as the linearized PAD-based PPCT technique in terms of their relative capabilities for tissue discrimination and characterization. Conclusions: This novel PPCT technique demonstrates great potential for biomedical imaging, especially for applications that require high spatial resolution and limited radiation exposure.« less

New Ways to Detect Pediatric Sickle Cell Retinopathy: A Comprehensive Review.

PubMed

Pahl, Daniel A; Green, Nancy S; Bhatia, Monica; Chen, Royce W S

2017-11-01

Sickle retinopathy reflects disease-related vascular injury of the eye, which can potentially result in visual loss from vitreous hemorrhage or retinal detachment. Here we review sickle retinopathy among children with sickle cell disease, describe the epidemiology, pediatric risk factors, pathophysiology, ocular findings, and treatment. Newer, more sensitive ophthalmological imaging modalities are available for retinal imaging, including ultra-widefield fluorescein angiography, spectral-domain optical coherence tomography, and optical coherence tomography angiography. Optical coherence tomography angiography provides a noninvasive view of retinal vascular layers that could previously not be imaged and can be quantified for comparative or prospective analyses. Ultra-widefield fluorescein angiography provides a more comprehensive view of the peripheral retina than traditional imaging techniques. Screening for retinopathy by standard fundoscopic imaging modalities detects a prevalence of approximately 10%. In contrast, these more sensitive methods allow for more sensitive examination that includes the retina perimeter where sickle retinopathy is often first detectable. Use of these new imaging modalities may detect a higher prevalence of early sickle pathology among children than has previously been reported. Earlier detection may help in better understanding the pathogenesis of sickle retinopathy and guide future screening and treatment paradigms.

Parallel traveling-wave MRI: a feasibility study.

PubMed

Pang, Yong; Vigneron, Daniel B; Zhang, Xiaoliang

2012-04-01

Traveling-wave magnetic resonance imaging utilizes far fields of a single-piece patch antenna in the magnet bore to generate radio frequency fields for imaging large-size samples, such as the human body. In this work, the feasibility of applying the "traveling-wave" technique to parallel imaging is studied using microstrip patch antenna arrays with both the numerical analysis and experimental tests. A specific patch array model is built and each array element is a microstrip patch antenna. Bench tests show that decoupling between two adjacent elements is better than -26-dB while matching of each element reaches -36-dB, demonstrating excellent isolation performance and impedance match capability. The sensitivity patterns are simulated and g-factors are calculated for both unloaded and loaded cases. The results on B 1- sensitivity patterns and g-factors demonstrate the feasibility of the traveling-wave parallel imaging. Simulations also suggest that different array configuration such as patch shape, position and orientation leads to different sensitivity patterns and g-factor maps, which provides a way to manipulate B(1) fields and improve the parallel imaging performance. The proposed method is also validated by using 7T MR imaging experiments. Copyright © 2011 Wiley-Liss, Inc.

Reduced field-of-view imaging for single-shot MRI with an amplitude-modulated chirp pulse excitation and Fourier transform reconstruction.

PubMed

Li, Jing; Zhang, Miao; Chen, Lin; Cai, Congbo; Sun, Huijun; Cai, Shuhui

2015-06-01

We employ an amplitude-modulated chirp pulse to selectively excite spins in one or more regions of interest (ROIs) to realize reduced field-of-view (rFOV) imaging based on single-shot spatiotemporally encoded (SPEN) sequence and Fourier transform reconstruction. The proposed rFOV imaging method was theoretically analyzed and illustrated with numerical simulation and tested with phantom experiments and in vivo rat experiments. In addition, point spread function was applied to demonstrate the feasibility of the proposed method. To evaluate the proposed method, the rFOV results were compared with those obtained using the EPI method with orthogonal RF excitation. The simulation and experimental results show that the proposed method can image one or two separated ROIs along the SPEN dimension in a single shot with higher spatial resolution, less sensitive to field inhomogeneity, and practically no aliasing artifacts. In addition, the proposed method may produce rFOV images with comparable signal-to-noise ratio to the rFOV EPI images. The proposed method is promising for the applications under severe susceptibility heterogeneities and for imaging separate ROIs simultaneously. Copyright © 2015 Elsevier Inc. All rights reserved.

Near-infrared Fluorescence Optical Imaging in Early Rheumatoid Arthritis: A Comparison to Magnetic Resonance Imaging and Ultrasonography.

PubMed

Krohn, Michaela; Ohrndorf, Sarah; Werner, Stephanie G; Schicke, Bernd; Burmester, Gerd-Rüdiger; Hamm, Bernd; Backhaus, Marina; Hermann, Kay-Geert A

2015-07-01

Near-infrared fluorescence optical imaging (FOI) is a novel imaging technology in the detection and evaluation of different arthritides. FOI was validated in comparison to magnetic resonance imaging (MRI), greyscale ultrasonography (GSUS), and power Doppler ultrasonography (PDUS) in patients with early rheumatoid arthritis (RA). Hands of 31 patients with early RA were examined by FOI, MRI, and US. In each modality, synovitis of the wrist, metacarpophalangeal joints (MCP) 2-5, and proximal interphalangeal joints (PIP) 2-5 were scored on a 4-point scale (0-3). Sensitivity and specificity of FOI were analyzed in comparison to MRI and US as reference methods, differentiating between 3 phases of FOI enhancement (P1-3). Intraclass correlation coefficients (ICC) were calculated to evaluate the agreement of FOI with MRI and US. A total of 279 joints (31 wrists, 124 MCP and 124 PIP joints) were evaluated. With MRI as the reference method, overall sensitivity/specificity of FOI was 0.81/0.00, 0.49/0.84, and 0.86/0.38 for wrist, MCP, and PIP joints, respectively. Under application of PDUS as reference, sensitivity was even higher, while specificity turned out to be low, except for MCP joints (0.88/0.15, 0.81/0.76, and 1.00/0.27, respectively). P2 appears to be the most sensitive FOI phase, while P1 showed the highest specificity. The best agreement of FOI was shown for PDUS, especially with regard to MCP and PIP joints (ICC of 0.57 and 0.53, respectively), while correlation with MRI was slightly lower. FOI remains an interesting diagnostic tool for patients with early RA, although this study revealed limitations concerning the detection of synovitis. Further research is needed to evaluate its full diagnostic potential in rheumatic diseases.

Preliminary Study on Appearance-Based Detection of Anatomical Point Landmarks in Body Trunk CT Images

NASA Astrophysics Data System (ADS)

Nemoto, Mitsutaka; Nomura, Yukihiro; Hanaoka, Shohei; Masutani, Yoshitaka; Yoshikawa, Takeharu; Hayashi, Naoto; Yoshioka, Naoki; Ohtomo, Kuni

Anatomical point landmarks as most primitive anatomical knowledge are useful for medical image understanding. In this study, we propose a detection method for anatomical point landmark based on appearance models, which include gray-level statistical variations at point landmarks and their surrounding area. The models are built based on results of Principal Component Analysis (PCA) of sample data sets. In addition, we employed generative learning method by transforming ROI of sample data. In this study, we evaluated our method with 24 data sets of body trunk CT images and obtained 95.8 ± 7.3 % of the average sensitivity in 28 landmarks.

Wear Detection of Drill Bit by Image-based Technique

NASA Astrophysics Data System (ADS)

Sukeri, Maziyah; Zulhilmi Paiz Ismadi, Mohd; Rahim Othman, Abdul; Kamaruddin, Shahrul

2018-03-01

Image processing for computer vision function plays an essential aspect in the manufacturing industries for the tool condition monitoring. This study proposes a dependable direct measurement method to measure the tool wear using image-based analysis. Segmentation and thresholding technique were used as the means to filter and convert the colour image to binary datasets. Then, the edge detection method was applied to characterize the edge of the drill bit. By using cross-correlation method, the edges of original and worn drill bits were correlated to each other. Cross-correlation graphs were able to detect the difference of the worn edge despite small difference between the graphs. Future development will focus on quantifying the worn profile as well as enhancing the sensitivity of the technique.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Foxley, Sean, E-mail: sean.foxley@ndcn.ox.ac.uk; Karczmar, Gregory S.; Domowicz, Miriam

Purpose: Widely used MRI methods show brain morphology both in vivo and ex vivo at very high resolution. Many of these methods (e.g., T{sub 2}{sup *}-weighted imaging, phase-sensitive imaging, or susceptibility-weighted imaging) are sensitive to local magnetic susceptibility gradients produced by subtle variations in tissue composition. However, the spectral resolution of commonly used methods is limited to maintain reasonable run-time combined with very high spatial resolution. Here, the authors report on data acquisition at increased spectral resolution, with 3-dimensional high spectral and spatial resolution MRI, in order to analyze subtle variations in water proton resonance frequency and lineshape that reflectmore » local anatomy. The resulting information compliments previous studies based on T{sub 2}{sup *} and resonance frequency. Methods: The proton free induction decay was sampled at high resolution and Fourier transformed to produce a high-resolution water spectrum for each image voxel in a 3D volume. Data were acquired using a multigradient echo pulse sequence (i.e., echo-planar spectroscopic imaging) with a spatial resolution of 50 × 50 × 70 μm{sup 3} and spectral resolution of 3.5 Hz. Data were analyzed in the spectral domain, and images were produced from the various Fourier components of the water resonance. This allowed precise measurement of local variations in water resonance frequency and lineshape, at the expense of significantly increased run time (16–24 h). Results: High contrast T{sub 2}{sup *}-weighted images were produced from the peak of the water resonance (peak height image), revealing a high degree of anatomical detail, specifically in the hippocampus and cerebellum. In images produced from Fourier components of the water resonance at −7.0 Hz from the peak, the contrast between deep white matter tracts and the surrounding tissue is the reverse of the contrast in water peak height images. This indicates the presence of a shoulder in the water resonance that is not present at +7.0 Hz and may be specific to white matter anatomy. Moreover, a frequency shift of 6.76 ± 0.55 Hz was measured between the molecular and granular layers of the cerebellum. This shift is demonstrated in corresponding spectra; water peaks from voxels in the molecular and granular layers are consistently 2 bins apart (7.0 Hz, as dictated by the spectral resolution) from one another. Conclusions: High spectral and spatial resolution MR imaging has the potential to accurately measure the changes in the water resonance in small voxels. This information can guide optimization and interpretation of more commonly used, more rapid imaging methods that depend on image contrast produced by local susceptibility gradients. In addition, with improved sampling methods, high spectral and spatial resolution data could be acquired in reasonable run times, and used for in vivo scans to increase sensitivity to variations in local susceptibility.« less

A Hybrid Method for Pancreas Extraction from CT Image Based on Level Set Methods

PubMed Central

Tan, Hanqing; Fujita, Hiroshi

2013-01-01

This paper proposes a novel semiautomatic method to extract the pancreas from abdominal CT images. Traditional level set and region growing methods that request locating initial contour near the final boundary of object have problem of leakage to nearby tissues of pancreas region. The proposed method consists of a customized fast-marching level set method which generates an optimal initial pancreas region to solve the problem that the level set method is sensitive to the initial contour location and a modified distance regularized level set method which extracts accurate pancreas. The novelty in our method is the proper selection and combination of level set methods, furthermore an energy-decrement algorithm and an energy-tune algorithm are proposed to reduce the negative impact of bonding force caused by connected tissue whose intensity is similar with pancreas. As a result, our method overcomes the shortages of oversegmentation at weak boundary and can accurately extract pancreas from CT images. The proposed method is compared to other five state-of-the-art medical image segmentation methods based on a CT image dataset which contains abdominal images from 10 patients. The evaluated results demonstrate that our method outperforms other methods by achieving higher accuracy and making less false segmentation in pancreas extraction. PMID:24066016

Wide-Field Imaging of Single-Nanoparticle Extinction with Sub-nm2 Sensitivity

NASA Astrophysics Data System (ADS)

Payne, Lukas M.; Langbein, Wolfgang; Borri, Paola

2018-03-01

We report on a highly sensitive wide-field imaging technique for quantitative measurement of the optical extinction cross section σext of single nanoparticles. The technique is simple and high speed, and it enables the simultaneous acquisition of hundreds of nanoparticles for statistical analysis. Using rapid referencing, fast acquisition, and a deconvolution analysis, a shot-noise-limited sensitivity down to 0.4 nm2 is achieved. Measurements on a set of individual gold nanoparticles of 5 nm diameter using this method yield σext=(10.0 ±3.1 ) nm2, which is consistent with theoretical expectations and well above the background fluctuations of 0.9 nm2 .

Inverse solutions for electrical impedance tomography based on conjugate gradients methods

NASA Astrophysics Data System (ADS)

Wang, M.

2002-01-01

A multistep inverse solution for two-dimensional electric field distribution is developed to deal with the nonlinear inverse problem of electric field distribution in relation to its boundary condition and the problem of divergence due to errors introduced by the ill-conditioned sensitivity matrix and the noise produced by electrode modelling and instruments. This solution is based on a normalized linear approximation method where the change in mutual impedance is derived from the sensitivity theorem and a method of error vector decomposition. This paper presents an algebraic solution of the linear equations at each inverse step, using a generalized conjugate gradients method. Limiting the number of iterations in the generalized conjugate gradients method controls the artificial errors introduced by the assumption of linearity and the ill-conditioned sensitivity matrix. The solution of the nonlinear problem is approached using a multistep inversion. This paper also reviews the mathematical and physical definitions of the sensitivity back-projection algorithm based on the sensitivity theorem. Simulations and discussion based on the multistep algorithm, the sensitivity coefficient back-projection method and the Newton-Raphson method are given. Examples of imaging gas-liquid mixing and a human hand in brine are presented.

Imaging of cartilage and bone: promises and pitfalls in clinical trials of osteoarthritis

PubMed Central

Eckstein, F.; Guermazi, A.; Gold, G.; Duryea, J.; Le Graverand, M.-P. Hellio; Wirth, W.; Miller, C.G.

2015-01-01

summary Imaging in clinical trials is used to evaluate subject eligibility, and/or efficacy of intervention, supporting decision making in drug development by ascertaining treatment effects on joint structure. This review focusses on imaging of bone and cartilage in clinical trials of (knee) osteoarthritis. We narratively review the full-text literature on imaging of bone and cartilage, adding primary experience in the implementation of imaging methods in clinical trials. Aims and constraints of applying imaging in clinical trials are outlined. The specific uses of semi-quantitative and quantitative imaging biomarkers of bone and cartilage in osteoarthritis trials are summarized, focusing on radiography and magnetic resonance imaging (MRI). Studies having compared both imaging methodologies directly and those having established a relationship between imaging biomarkers and clinical outcomes are highlighted. To make this review of practical use, recommendations are provided as to which imaging protocols are ideal for capturing specific aspects of bone and cartilage tissue, and pitfalls in their usage are highlighted. Further, the longitudinal sensitivity to change, of different imaging methods is reported for various patient strata. From these power calculations can be accomplished, provided the strength of the treatment effect is known. In conclusion, current imaging methodologies provide powerful tools for scoring and measuring morphological and compositional aspects of most articular tissues, capturing longitudinal change with reasonable to excellent sensitivity. When employed properly, imaging has tremendous potential for ascertaining treatment effects on various joint structures, potentially over shorter time scales than required for demonstrating effects on clinical outcomes. PMID:25278061

Iron Oxide Nanoparticle-Micelles (ION-Micelles) for Sensitive (Molecular) Magnetic Particle Imaging and Magnetic Resonance Imaging

PubMed Central

Starmans, Lucas W. E.; Burdinski, Dirk; Haex, Nicole P. M.; Moonen, Rik P. M.; Strijkers, Gustav J.; Nicolay, Klaas; Grüll, Holger

2013-01-01

Background Iron oxide nanoparticles (IONs) are a promising nanoplatform for contrast-enhanced MRI. Recently, magnetic particle imaging (MPI) was introduced as a new imaging modality, which is able to directly visualize magnetic particles and could serve as a more sensitive and quantitative alternative to MRI. However, MPI requires magnetic particles with specific magnetic properties for optimal use. Current commercially available iron oxide formulations perform suboptimal in MPI, which is triggering research into optimized synthesis strategies. Most synthesis procedures aim at size control of iron oxide nanoparticles rather than control over the magnetic properties. In this study, we report on the synthesis, characterization and application of a novel ION platform for sensitive MPI and MRI. Methods and Results IONs were synthesized using a thermal-decomposition method and subsequently phase-transferred by encapsulation into lipidic micelles (ION-Micelles). Next, the material and magnetic properties of the ION-Micelles were analyzed. Most notably, vibrating sample magnetometry measurements showed that the effective magnetic core size of the IONs is 16 nm. In addition, magnetic particle spectrometry (MPS) measurements were performed. MPS is essentially zero-dimensional MPI and therefore allows to probe the potential of iron oxide formulations for MPI. ION-Micelles induced up to 200 times higher signal in MPS measurements than commercially available iron oxide formulations (Endorem, Resovist and Sinerem) and thus likely allow for significantly more sensitive MPI. In addition, the potential of the ION-Micelle platform for molecular MPI and MRI was showcased by MPS and MRI measurements of fibrin-binding peptide functionalized ION-Micelles (FibPep-ION-Micelles) bound to blood clots. Conclusions The presented data underlines the potential of the ION-Micelle nanoplatform for sensitive (molecular) MPI and warrants further investigation of the FibPep-ION-Micelle platform for in vivo, non-invasive imaging of fibrin in preclinical disease models of thrombus-related pathologies and atherosclerosis. PMID:23437371

Towards the low-dose characterization of beam sensitive nanostructures via implementation of sparse image acquisition in scanning transmission electron microscopy

NASA Astrophysics Data System (ADS)

Hwang, Sunghwan; Han, Chang Wan; Venkatakrishnan, Singanallur V.; Bouman, Charles A.; Ortalan, Volkan

2017-04-01

Scanning transmission electron microscopy (STEM) has been successfully utilized to investigate atomic structure and chemistry of materials with atomic resolution. However, STEM’s focused electron probe with a high current density causes the electron beam damages including radiolysis and knock-on damage when the focused probe is exposed onto the electron-beam sensitive materials. Therefore, it is highly desirable to decrease the electron dose used in STEM for the investigation of biological/organic molecules, soft materials and nanomaterials in general. With the recent emergence of novel sparse signal processing theories, such as compressive sensing and model-based iterative reconstruction, possibilities of operating STEM under a sparse acquisition scheme to reduce the electron dose have been opened up. In this paper, we report our recent approach to implement a sparse acquisition in STEM mode executed by a random sparse-scan and a signal processing algorithm called model-based iterative reconstruction (MBIR). In this method, a small portion, such as 5% of randomly chosen unit sampling areas (i.e. electron probe positions), which corresponds to pixels of a STEM image, within the region of interest (ROI) of the specimen are scanned with an electron probe to obtain a sparse image. Sparse images are then reconstructed using the MBIR inpainting algorithm to produce an image of the specimen at the original resolution that is consistent with an image obtained using conventional scanning methods. Experimental results for down to 5% sampling show consistency with the full STEM image acquired by the conventional scanning method. Although, practical limitations of the conventional STEM instruments, such as internal delays of the STEM control electronics and the continuous electron gun emission, currently hinder to achieve the full potential of the sparse acquisition STEM in realizing the low dose imaging condition required for the investigation of beam-sensitive materials, the results obtained in our experiments demonstrate the sparse acquisition STEM imaging is potentially capable of reducing the electron dose by at least 20 times expanding the frontiers of our characterization capabilities for investigation of biological/organic molecules, polymers, soft materials and nanostructures in general.

Statistical and fractal analysis of autofluorescent myocardium images in posthumous diagnostics of acute coronary insufficiency

NASA Astrophysics Data System (ADS)

Boichuk, T. M.; Bachinskiy, V. T.; Vanchuliak, O. Ya.; Minzer, O. P.; Garazdiuk, M.; Motrich, A. V.

2014-08-01

This research presents the results of investigation of laser polarization fluorescence of biological layers (histological sections of the myocardium). The polarized structure of autofluorescence imaging layers of biological tissues was detected and investigated. Proposed the model of describing the formation of polarization inhomogeneous of autofluorescence imaging biological optically anisotropic layers. On this basis, analytically and experimentally tested to justify the method of laser polarimetry autofluorescent. Analyzed the effectiveness of this method in the postmortem diagnosis of infarction. The objective criteria (statistical moments) of differentiation of autofluorescent images of histological sections myocardium were defined. The operational characteristics (sensitivity, specificity, accuracy) of these technique were determined.

Phase-contrast x-ray computed tomography for observing biological specimens and organic materials

NASA Astrophysics Data System (ADS)

Momose, Atsushi; Takeda, Tohoru; Itai, Yuji

1995-02-01

A novel three-dimensional x-ray imaging method has been developed by combining a phase-contrast x-ray imaging technique with x-ray computed tomography. This phase-contrast x-ray computed tomography (PCX-CT) provides sectional images of organic specimens that would produce absorption-contrast x-ray CT images with little contrast. Comparing PCX-CT images of rat cerebellum and cancerous rabbit liver specimens with corresponding absorption-contrast CT images shows that PCX-CT is much more sensitive to the internal structure of organic specimens.

Mini gamma camera, camera system and method of use

DOEpatents

Majewski, Stanislaw; Weisenberger, Andrew G.; Wojcik, Randolph F.

2001-01-01

A gamma camera comprising essentially and in order from the front outer or gamma ray impinging surface: 1) a collimator, 2) a scintillator layer, 3) a light guide, 4) an array of position sensitive, high resolution photomultiplier tubes, and 5) printed circuitry for receipt of the output of the photomultipliers. There is also described, a system wherein the output supplied by the high resolution, position sensitive photomultipiler tubes is communicated to: a) a digitizer and b) a computer where it is processed using advanced image processing techniques and a specific algorithm to calculate the center of gravity of any abnormality observed during imaging, and c) optional image display and telecommunications ports.

High resolution laboratory grating-based x-ray phase-contrast CT

NASA Astrophysics Data System (ADS)

Viermetz, Manuel P.; Birnbacher, Lorenz J. B.; Fehringer, Andreas; Willner, Marian; Noel, Peter B.; Pfeiffer, Franz; Herzen, Julia

2017-03-01

Grating-based phase-contrast computed tomography (gbPC-CT) is a promising imaging method for imaging of soft tissue contrast without the need of any contrast agent. The focus of this study is the increase in spatial resolution without loss in sensitivity to allow visualization of pathologies comparable to the convincing results obtained at the synchrotron. To improve the effective pixel size a super-resolution reconstruction based on subpixel shifts involving a deconvolution of the image is applied on differential phase-contrast data. In our study we could achieve an effective pixel sizes of 28mm without any drawback in terms of sensitivity or the ability to measure quantitative data.

A parameterized logarithmic image processing method with Laplacian of Gaussian filtering for lung nodule enhancement in chest radiographs.

PubMed

Chen, Sheng; Yao, Liping; Chen, Bao

2016-11-01

The enhancement of lung nodules in chest radiographs (CXRs) plays an important role in the manual as well as computer-aided detection (CADe) lung cancer. In this paper, we proposed a parameterized logarithmic image processing (PLIP) method combined with the Laplacian of a Gaussian (LoG) filter to enhance lung nodules in CXRs. We first applied several LoG filters with varying parameters to an original CXR to enhance the nodule-like structures as well as the edges in the image. We then applied the PLIP model, which can enhance lung nodule images with high contrast and was beneficial in extracting effective features for nodule detection in the CADe scheme. Our method combined the advantages of both the PLIP algorithm and the LoG algorithm, which can enhance lung nodules in chest radiographs with high contrast. To test our nodule enhancement method, we tested a CADe scheme, with a relatively high performance in nodule detection, using a publically available database containing 140 nodules in 140 CXRs enhanced through our nodule enhancement method. The CADe scheme attained a sensitivity of 81 and 70 % with an average of 5.0 frame rate (FP) and 2.0 FP, respectively, in a leave-one-out cross-validation test. By contrast, the CADe scheme based on the original image recorded a sensitivity of 77 and 63 % at 5.0 FP and 2.0 FP, respectively. We introduced the measurement of enhancement by entropy evaluation to objectively assess our method. Experimental results show that the proposed method obtains an effective enhancement of lung nodules in CXRs for both radiologists and CADe schemes.

No-reference image quality assessment based on statistics of convolution feature maps

NASA Astrophysics Data System (ADS)

Lv, Xiaoxin; Qin, Min; Chen, Xiaohui; Wei, Guo

2018-04-01

We propose a Convolutional Feature Maps (CFM) driven approach to accurately predict image quality. Our motivation bases on the finding that the Nature Scene Statistic (NSS) features on convolution feature maps are significantly sensitive to distortion degree of an image. In our method, a Convolutional Neural Network (CNN) is trained to obtain kernels for generating CFM. We design a forward NSS layer which performs on CFM to better extract NSS features. The quality aware features derived from the output of NSS layer is effective to describe the distortion type and degree an image suffered. Finally, a Support Vector Regression (SVR) is employed in our No-Reference Image Quality Assessment (NR-IQA) model to predict a subjective quality score of a distorted image. Experiments conducted on two public databases demonstrate the promising performance of the proposed method is competitive to state of the art NR-IQA methods.

An inductive method for automatic generation of referring physician prefetch rules for PACS.

PubMed

Okura, Yasuhiko; Matsumura, Yasushi; Harauchi, Hajime; Sukenobu, Yoshiharu; Kou, Hiroko; Kohyama, Syunsuke; Yasuda, Norihiro; Yamamoto, Yuichiro; Inamura, Kiyonari

2002-12-01

To prefetch images in a hospital-wide picture archiving and communication system (PACS), a rule must be devised to permit accurate selection of examinations in which a patient's images are stored. We developed an inductive method to compose prefetch rules from practical data which were obtained in a hospital using a decision tree algorithm. Our methods were evaluated on data acquired in Osaka University Hospital for one month. The data collected consisted of 58,617 cases of consultation reservations, 643,797 examination histories of patients, and 323,993 records of image requests in PACS. Four parameters indicating whether the images of the patient were requested or not for each consultation reservation were derived from the database. As a result, the successful selection sensitivity for consultations in which images were requested was approximately 0.8, and the specificity for excluding consultations accurately where images were not requested was approximately 0.7.

The x-ray time of flight method for investigation of ghosting in amorphous selenium-based flat panel medical x-ray imagers.

PubMed

Rau, A W; Bakueva, L; Rowlands, J A

2005-10-01

Amorphous selenium (a-Se) based real-time flat-panel imagers (FPIs) are finding their way into the digital radiology department because they offer the practical advantages of digital x-ray imaging combined with an image quality that equals or outperforms that of conventional systems. The temporal imaging characteristics of FPIs can be affected by ghosting (i.e., radiation-induced changes of sensitivity) when the dose to the detector is high (e.g., portal imaging and mammography) or the images are acquired at a high frame rate (e.g., fluoroscopy). In this paper, the x-ray time-of-flight (TOF) method is introduced as a tool for the investigation of ghosting in a-Se photoconductor layers. The method consists of irradiating layers of a-Se with short x-ray pulses. From the current generated in the a-Se layer, ghosting is quantified and the ghosting parameters (charge carrier generation rate and carrier lifetimes and mobilities) are assessed. The x-ray TOF method is novel in that (1) x-ray sensitivity (S) and ghosting parameters can be measured simultaneously, (2) the transport of both holes and electrons can be isolated, and (3) the method is applicable to the practical a-Se layer structure with blocking contacts used in FPIs. The x-ray TOF method was applied to an analysis of ghosting in a-Se photoconductor layers under portal imaging conditions, i.e., 1 mm thick a-Se layers, biased at 5 V/ microm, were irradiated using a 6 MV LINAC x-ray beam to a total dose (ghosting dose) of 30 Gy. The initial sensitivity (S0) of the a-Se layers was 63 +/- 2 nC cm(-2) cGy(-1). It was found that S decreases to 30% of S0 after a ghosting dose of 5 Gy and to 21% after 30 Gy at which point no further change in S occurs. At an x-ray intensity of 22 Gy/s (instantaneous dose rate during a LINAC x-ray pulse), the charge carrier generation rate was 1.25 +/- 0.1 x 10(22) ehp m(-3) s(-1) and, to a first approximation, independent of the ghosting dose. However, both hole and electron transport showed a strong dependence on the ghosting dose: hole transport decreased by 61%, electron transport by up to approximately 80%. Therefore, degradation of both hole and electron transport due to the recombination of mobile charge carriers with trapped carriers (of opposite polarity) were identified as the main cause of ghosting in this study.

Recovery and normalization of triple coincidences in PET.

PubMed

Lage, Eduardo; Parot, Vicente; Moore, Stephen C; Sitek, Arkadiusz; Udías, Jose M; Dave, Shivang R; Park, Mi-Ae; Vaquero, Juan J; Herraiz, Joaquin L

2015-03-01

Triple coincidences in positron emission tomography (PET) are events in which three γ-rays are detected simultaneously. These events, though potentially useful for enhancing the sensitivity of PET scanners, are discarded or processed without special consideration in current systems, because there is not a clear criterion for assigning them to a unique line-of-response (LOR). Methods proposed for recovering such events usually rely on the use of highly specialized detection systems, hampering general adoption, and/or are based on Compton-scatter kinematics and, consequently, are limited in accuracy by the energy resolution of standard PET detectors. In this work, the authors propose a simple and general solution for recovering triple coincidences, which does not require specialized detectors or additional energy resolution requirements. To recover triple coincidences, the authors' method distributes such events among their possible LORs using the relative proportions of double coincidences in these LORs. The authors show analytically that this assignment scheme represents the maximum-likelihood solution for the triple-coincidence distribution problem. The PET component of a preclinical PET/CT scanner was adapted to enable the acquisition and processing of triple coincidences. Since the efficiencies for detecting double and triple events were found to be different throughout the scanner field-of-view, a normalization procedure specific for triple coincidences was also developed. The effect of including triple coincidences using their method was compared against the cases of equally weighting the triples among their possible LORs and discarding all the triple events. The authors used as figures of merit for this comparison sensitivity, noise-equivalent count (NEC) rates and image quality calculated as described in the NEMA NU-4 protocol for the assessment of preclinical PET scanners. The addition of triple-coincidence events with the authors' method increased peak NEC rates of the scanner by 26.6% and 32% for mouse- and rat-sized objects, respectively. This increase in NEC-rate performance was also reflected in the image-quality metrics. Images reconstructed using double and triple coincidences recovered using their method had better signal-to-noise ratio than those obtained using only double coincidences, while preserving spatial resolution and contrast. Distribution of triple coincidences using an equal-weighting scheme increased apparent system sensitivity but degraded image quality. The performance boost provided by the inclusion of triple coincidences using their method allowed to reduce the acquisition time of standard imaging procedures by up to ∼25%. Recovering triple coincidences with the proposed method can effectively increase the sensitivity of current clinical and preclinical PET systems without compromising other parameters like spatial resolution or contrast.

Computerized analysis of sonograms for the detection of breast lesions

NASA Astrophysics Data System (ADS)

Drukker, Karen; Giger, Maryellen L.; Horsch, Karla; Vyborny, Carl J.

2002-05-01

With a renewed interest in using non-ionizing radiation for the screening of high risk women, there is a clear role for a computerized detection aid in ultrasound. Thus, we are developing a computerized detection method for the localization of lesions on breast ultrasound images. The computerized detection scheme utilizes two methods. Firstly, a radial gradient index analysis is used to distinguish potential lesions from normal parenchyma. Secondly, an image skewness analysis is performed to identify posterior acoustic shadowing. We analyzed 400 cases (757 images) consisting of complex cysts, solid benign lesions, and malignant lesions. The detection method yielded an overall sensitivity of 95% by image, and 99% by case at a false-positive rate of 0.94 per image. In 51% of all images, only the lesion itself was detected, while in 5% of the images only the shadowing was identified. For malignant lesions these numbers were 37% and 9%, respectively. In summary, we have developed a computer detection method for lesions on ultrasound images of the breast, which may ultimately aid in breast cancer screening.

New cardiac cameras: single-photon emission CT and PET.

PubMed

Slomka, Piotr J; Berman, Daniel S; Germano, Guido

2014-07-01

Nuclear cardiology instrumentation has evolved significantly in the recent years. Concerns about radiation dose and long acquisition times have propelled developments of dedicated high-efficiency cardiac SPECT scanners. Novel collimator designs, such as multipinhole or locally focusing collimators arranged in geometries that are optimized for cardiac imaging, have been implemented to enhance photon-detection sensitivity. Some of these new SPECT scanners use solid-state photon detectors instead of photomultipliers to improve image quality and to reduce the scanner footprint. These new SPECT devices allow dramatic up to 7-fold reduction in acquisition times or similar reduction in radiation dose. In addition, new hardware for photon attenuation correction allowing ultralow radiation doses has been offered by some vendors. To mitigate photon attenuation artifacts for the new SPECT scanners not equipped with attenuation correction hardware, 2-position (upright-supine or prone-supine) imaging has been proposed. PET hardware developments have been primarily driven by the requirements of oncologic imaging, but cardiac imaging can benefit from improved PET image quality and improved sensitivity of 3D systems. The time-of-flight reconstruction combined with resolution recovery techniques is now implemented by all major PET vendors. These new methods improve image contrast and image resolution and reduce image noise. High-sensitivity 3D PET without interplane septa allows reduced radiation dose for cardiac perfusion imaging. Simultaneous PET/MR hybrid system has been developed. Solid-state PET detectors with avalanche photodiodes or digital silicon photomultipliers have been introduced, and they offer improved imaging characteristics and reduced sensitivity to electromagnetic MR fields. Higher maximum count rate of the new PET detectors allows routine first-pass Rb-82 imaging, with 3D PET acquisition enabling clinical utilization of dynamic imaging with myocardial flow measurements for this tracer. The availability of high-end CT component in most PET/CT configurations enables hybrid multimodality cardiac imaging protocols with calcium scoring or CT angiography or both. Copyright © 2014. Published by Elsevier Inc.

Cascade classification of endocytoscopic images of colorectal lesions for automated pathological diagnosis

NASA Astrophysics Data System (ADS)

Itoh, Hayato; Mori, Yuichi; Misawa, Masashi; Oda, Masahiro; Kudo, Shin-ei; Mori, Kensaku

2018-02-01

This paper presents a new classification method for endocytoscopic images. Endocytoscopy is a new endoscope that enables us to perform conventional endoscopic observation and ultramagnified observation of cell level. This ultramagnified views (endocytoscopic images) make possible to perform pathological diagnosis only on endo-scopic views of polyps during colonoscopy. However, endocytoscopic image diagnosis requires higher experiences for physicians. An automated pathological diagnosis system is required to prevent the overlooking of neoplastic lesions in endocytoscopy. For this purpose, we propose a new automated endocytoscopic image classification method that classifies neoplastic and non-neoplastic endocytoscopic images. This method consists of two classification steps. At the first step, we classify an input image by support vector machine. We forward the image to the second step if the confidence of the first classification is low. At the second step, we classify the forwarded image by convolutional neural network. We reject the input image if the confidence of the second classification is also low. We experimentally evaluate the classification performance of the proposed method. In this experiment, we use about 16,000 and 4,000 colorectal endocytoscopic images as training and test data, respectively. The results show that the proposed method achieves high sensitivity 93.4% with small rejection rate 9.3% even for difficult test data.

Organic-on-silicon complementary metal-oxide-semiconductor colour image sensors.

PubMed

Lim, Seon-Jeong; Leem, Dong-Seok; Park, Kyung-Bae; Kim, Kyu-Sik; Sul, Sangchul; Na, Kyoungwon; Lee, Gae Hwang; Heo, Chul-Joon; Lee, Kwang-Hee; Bulliard, Xavier; Satoh, Ryu-Ichi; Yagi, Tadao; Ro, Takkyun; Im, Dongmo; Jung, Jungkyu; Lee, Myungwon; Lee, Tae-Yon; Han, Moon Gyu; Jin, Yong Wan; Lee, Sangyoon

2015-01-12

Complementary metal-oxide-semiconductor (CMOS) colour image sensors are representative examples of light-detection devices. To achieve extremely high resolutions, the pixel sizes of the CMOS image sensors must be reduced to less than a micron, which in turn significantly limits the number of photons that can be captured by each pixel using silicon (Si)-based technology (i.e., this reduction in pixel size results in a loss of sensitivity). Here, we demonstrate a novel and efficient method of increasing the sensitivity and resolution of the CMOS image sensors by superposing an organic photodiode (OPD) onto a CMOS circuit with Si photodiodes, which consequently doubles the light-input surface area of each pixel. To realise this concept, we developed organic semiconductor materials with absorption properties selective to green light and successfully fabricated highly efficient green-light-sensitive OPDs without colour filters. We found that such a top light-receiving OPD, which is selective to specific green wavelengths, demonstrates great potential when combined with a newly designed Si-based CMOS circuit containing only blue and red colour filters. To demonstrate the effectiveness of this state-of-the-art hybrid colour image sensor, we acquired a real full-colour image using a camera that contained the organic-on-Si hybrid CMOS colour image sensor.

Organic-on-silicon complementary metal–oxide–semiconductor colour image sensors

PubMed Central

Lim, Seon-Jeong; Leem, Dong-Seok; Park, Kyung-Bae; Kim, Kyu-Sik; Sul, Sangchul; Na, Kyoungwon; Lee, Gae Hwang; Heo, Chul-Joon; Lee, Kwang-Hee; Bulliard, Xavier; Satoh, Ryu-Ichi; Yagi, Tadao; Ro, Takkyun; Im, Dongmo; Jung, Jungkyu; Lee, Myungwon; Lee, Tae-Yon; Han, Moon Gyu; Jin, Yong Wan; Lee, Sangyoon

2015-01-01

Complementary metal–oxide–semiconductor (CMOS) colour image sensors are representative examples of light-detection devices. To achieve extremely high resolutions, the pixel sizes of the CMOS image sensors must be reduced to less than a micron, which in turn significantly limits the number of photons that can be captured by each pixel using silicon (Si)-based technology (i.e., this reduction in pixel size results in a loss of sensitivity). Here, we demonstrate a novel and efficient method of increasing the sensitivity and resolution of the CMOS image sensors by superposing an organic photodiode (OPD) onto a CMOS circuit with Si photodiodes, which consequently doubles the light-input surface area of each pixel. To realise this concept, we developed organic semiconductor materials with absorption properties selective to green light and successfully fabricated highly efficient green-light-sensitive OPDs without colour filters. We found that such a top light-receiving OPD, which is selective to specific green wavelengths, demonstrates great potential when combined with a newly designed Si-based CMOS circuit containing only blue and red colour filters. To demonstrate the effectiveness of this state-of-the-art hybrid colour image sensor, we acquired a real full-colour image using a camera that contained the organic-on-Si hybrid CMOS colour image sensor. PMID:25578322

A theoretical-experimental methodology for assessing the sensitivity of biomedical spectral imaging platforms, assays, and analysis methods.

PubMed

Leavesley, Silas J; Sweat, Brenner; Abbott, Caitlyn; Favreau, Peter; Rich, Thomas C

2018-01-01

Spectral imaging technologies have been used for many years by the remote sensing community. More recently, these approaches have been applied to biomedical problems, where they have shown great promise. However, biomedical spectral imaging has been complicated by the high variance of biological data and the reduced ability to construct test scenarios with fixed ground truths. Hence, it has been difficult to objectively assess and compare biomedical spectral imaging assays and technologies. Here, we present a standardized methodology that allows assessment of the performance of biomedical spectral imaging equipment, assays, and analysis algorithms. This methodology incorporates real experimental data and a theoretical sensitivity analysis, preserving the variability present in biomedical image data. We demonstrate that this approach can be applied in several ways: to compare the effectiveness of spectral analysis algorithms, to compare the response of different imaging platforms, and to assess the level of target signature required to achieve a desired performance. Results indicate that it is possible to compare even very different hardware platforms using this methodology. Future applications could include a range of optimization tasks, such as maximizing detection sensitivity or acquisition speed, providing high utility for investigators ranging from design engineers to biomedical scientists. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Multi-angle nuclear imaging apparatus and method

DOEpatents

Anger, Hal O. [Berkeley, CA

1980-04-08

Nuclear imaging apparatus for obtaining multi-plane readouts of radioactive material in a human or animal subject. A probe disposed in the vicinity of the subject is provided for receiving radiation from radiating sources in the subject and for forming a probe radiation image. The probe has a collimator with different portions thereof having holes disposed at different angles. A single scintillation crystal overlies the collimator for receiving radiation passing through the collimator and producing scintillations to provide the probe image. An array of photomultiplier tubes overlie the single crystal for observing the probe image and providing electrical outputs. Conversion apparatus is provided for converting the electrical outputs representing the probe image into optical images displayed on the screen of a cathode ray tube. Divider apparatus is provided for dividing the probe radiation image into a plurality of areas with the areas corresponding to different portions of the collimator having holes disposed at different angles. A light sensitive medium is provided for receiving optical images. Apparatus is provided for causing relative movement between the probe and the subject. Apparatus is also provided for causing relative movement between the optical image on the screen and the light sensitive medium which corresponds to the relative movement between the probe and the subject whereby there is produced on the light sensitive medium a plurality of images that portray the subject as seen from different angles corresponding to the portions of the collimator having holes at different angles.

Multi-angle nuclear imaging apparatus and method

DOEpatents

Anger, H.O.

1980-04-08

A nuclear imaging apparatus is described for obtaining multi-plane readouts of radioactive material in a human or animal subject. A probe disposed in the vicinity of the subject is provided for receiving radiation from radiating sources in the subject and for forming a probe radiation image. The probe has a collimator with different portions having holes disposed at different angles. A single scintillation crystal overlies the collimator for receiving radiation passing through the collimator and producing scintillations to provide the probe image. An array of photomultiplier tubes overlie the single crystal for observing the probe image and providing electrical outputs. Conversion apparatus is provided for converting the electrical outputs representing the probe image into optical images displayed on the screen of a cathode ray tube. Divider apparatus is provided for dividing the probe radiation image into a plurality of areas with the areas corresponding to different portions of the collimator having holes disposed at different angles. A light sensitive medium is provided for receiving optical images. Apparatus is provided for causing relative movement between the probe and the subject. Apparatus is also provided for causing relative movement between the optical image on the screen and the light sensitive medium which corresponds to the relative movement between the probe and the subject whereby there is produced on the light sensitive medium a plurality of images that portray the subject as seen from different angles corresponding to the portions of the collimator having holes at different angles. 11 figs.

Diagnostic accuracy of [99mTc]Tc-Sestamibi in the assessment of thyroid nodules

PubMed Central

Yordanova, Anna; Mahjoob, Soha; Lingohr, Philipp; Kalff, Jörg; Türler, Andreas; Palmedo, Holger; Biersack, Hans-Jürgen; Kristiansen, Glen; Farahati, Jamshid; Essler, Markus; Ahmadzadehfar, Hojjat

2017-01-01

[99mTc]Tc-Sestamibi (MIBI) is an increasingly used tool for evaluation of thyroid nodules. However, there is a lack of evidence about the accuracy of this method in the European population. The aim of this study was to assess the utility of MIBI for the differentiation of thyroid nodules in a large cohort. 161 patients underwent MIBI, followed by a thyroidectomy. We used a dual phase MIBI protocol. Interpretation of the images included a scoring system from 0 (absent) to 3 (increased); this was to provide a scale for the uptake of the thyroid nodule in comparison to the paranodular tissue. Additionally, we evaluated the tracer uptake trend in late images compared to early images. We used the final histopathology as the reference standard. Scores 0-1 in early images, scores 0-2 in late images, and an absence of increasing uptake in the thyroid nodule in late images, showed the best predictive values to exclude malignancy, respectively (negative predictive value (NPV) 89%). Highest sensitivity (91%) for malignant nodules was evident in early images with a score 1-3. Highest specificity (91%) was obtained when the negative was defined as an absence of uptake-increase, in the late images. This study confirms that the most valuable feature of MIBI is the high NPV. Thus, with the appropriate interpretation method, high sensitivity and specificity, and moderate PPV can be obtained. PMID:29212258

Diagnostic accuracy of [99mTc]Tc-Sestamibi in the assessment of thyroid nodules.

PubMed

Yordanova, Anna; Mahjoob, Soha; Lingohr, Philipp; Kalff, Jörg; Türler, Andreas; Palmedo, Holger; Biersack, Hans-Jürgen; Kristiansen, Glen; Farahati, Jamshid; Essler, Markus; Ahmadzadehfar, Hojjat

2017-11-07

[ 99m Tc]Tc-Sestamibi (MIBI) is an increasingly used tool for evaluation of thyroid nodules. However, there is a lack of evidence about the accuracy of this method in the European population. The aim of this study was to assess the utility of MIBI for the differentiation of thyroid nodules in a large cohort. 161 patients underwent MIBI, followed by a thyroidectomy. We used a dual phase MIBI protocol. Interpretation of the images included a scoring system from 0 (absent) to 3 (increased); this was to provide a scale for the uptake of the thyroid nodule in comparison to the paranodular tissue. Additionally, we evaluated the tracer uptake trend in late images compared to early images. We used the final histopathology as the reference standard. Scores 0-1 in early images, scores 0-2 in late images, and an absence of increasing uptake in the thyroid nodule in late images, showed the best predictive values to exclude malignancy, respectively (negative predictive value (NPV) 89%). Highest sensitivity (91%) for malignant nodules was evident in early images with a score 1-3. Highest specificity (91%) was obtained when the negative was defined as an absence of uptake-increase, in the late images. This study confirms that the most valuable feature of MIBI is the high NPV. Thus, with the appropriate interpretation method, high sensitivity and specificity, and moderate PPV can be obtained.

X-ray Moiré deflectometry using synthetic reference images

DOE PAGES

Stutman, Dan; Valdivia, Maria Pia; Finkenthal, Michael

2015-06-25

Moiré fringe deflectometry with grating interferometers is a technique that enables refraction-based x-ray imaging using a single exposure of an object. To obtain the refraction image, the method requires a reference fringe pattern (without the object). Our study shows that, in order to avoid artifacts, the reference pattern must be exactly matched in phase with the object fringe pattern. In experiments, however, it is difficult to produce a perfectly matched reference pattern due to unavoidable interferometer drifts. We present a simple method to obtain matched reference patterns using a phase-scan procedure to generate synthetic Moiré images. As a result, themore » method will enable deflectometric diagnostics of transient phenomena such as laser-produced plasmas and could improve the sensitivity and accuracy of medical phase-contrast imaging.« less

Breast EIT using a new projected image reconstruction method with multi-frequency measurements.

PubMed

Lee, Eunjung; Ts, Munkh-Erdene; Seo, Jin Keun; Woo, Eung Je

2012-05-01

We propose a new method to produce admittivity images of the breast for the diagnosis of breast cancer using electrical impedance tomography(EIT). Considering the anatomical structure of the breast, we designed an electrode configuration where current-injection and voltage-sensing electrodes are separated in such a way that internal current pathways are approximately along the tangential direction of an array of voltage-sensing electrodes. Unlike conventional EIT imaging methods where the number of injected currents is maximized to increase the total amount of measured data, current is injected only twice between two pairs of current-injection electrodes attached along the circumferential side of the breast. For each current injection, the induced voltages are measured from the front surface of the breast using as many voltage-sensing electrodes as possible. Although this electrode configurational lows us to measure induced voltages only on the front surface of the breast,they are more sensitive to an anomaly inside the breast since such an injected current tends to produce a more uniform internal current density distribution. Furthermore, the sensitivity of a measured boundary voltage between two equipotential lines on the front surface of the breast is improved since those equipotential lines are perpendicular to the primary direction of internal current streamlines. One should note that this novel data collection method is different from those of other frontal plane techniques such as the x-ray projection and T-scan imaging methods because we do not get any data on the plane that is perpendicular to the current flow. To reconstruct admittivity images using two measured voltage data sets, a new projected image reconstruction algorithm is developed. Numerical simulations demonstrate the frequency-difference EIT imaging of the breast. The results show that the new method is promising to accurately detect and localize small anomalies inside the breast.

Evaluation of diffusivity in the anterior lobe of the pituitary gland: 3D turbo field echo with diffusion-sensitized driven-equilibrium preparation.

PubMed

Hiwatashi, A; Yoshiura, T; Togao, O; Yamashita, K; Kikuchi, K; Kobayashi, K; Ohga, M; Sonoda, S; Honda, H; Obara, M

2014-01-01

3D turbo field echo with diffusion-sensitized driven-equilibrium preparation is a non-echo-planar technique for DWI, which enables high-resolution DWI without field inhomogeneity-related image distortion. The purpose of this study was to evaluate the feasibility of diffusion-sensitized driven-equilibrium turbo field echo in evaluating diffusivity in the normal pituitary gland. First, validation of diffusion-sensitized driven-equilibrium turbo field echo was attempted by comparing it with echo-planar DWI. Five healthy volunteers were imaged by using diffusion-sensitized driven-equilibrium turbo field echo and echo-planar DWI. The imaging voxel size was 1.5 × 1.5 × 1.5 mm(3) for diffusion-sensitized driven-equilibrium turbo field echo and 1.5 × 1.9 × 3.0 mm(3) for echo-planar DWI. ADCs measured by the 2 methods in 15 regions of interests (6 in gray matter and 9 in white matter) were compared by using the Pearson correlation coefficient. The ADC in the pituitary anterior lobe was then measured in 10 volunteers by using diffusion-sensitized driven-equilibrium turbo field echo, and the results were compared with those in the pons and vermis by using a paired t test. The ADCs from the 2 methods showed a strong correlation (r = 0.79; P < .0001), confirming the accuracy of the ADC measurement with the diffusion-sensitized driven-equilibrium sequence. The ADCs in the normal pituitary gland were 1.37 ± 0.13 × 10(-3) mm(2)/s, which were significantly higher than those in the pons (1.01 ± 0.24 × 10(-3) mm(2)/s) and the vermis (0.89 ± 0.25 × 10(-3) mm(2)/s, P < .01). We demonstrated that diffusion-sensitized driven-equilibrium turbo field echo is feasible in assessing ADC in the pituitary gland.

Adaptive optimization of reference intensity for optical coherence imaging using galvanometric mirror tilting method

NASA Astrophysics Data System (ADS)

Kim, Ji-hyun; Han, Jae-Ho; Jeong, Jichai

2015-09-01

Integration time and reference intensity are important factors for achieving high signal-to-noise ratio (SNR) and sensitivity in optical coherence tomography (OCT). In this context, we present an adaptive optimization method of reference intensity for OCT setup. The reference intensity is automatically controlled by tilting a beam position using a Galvanometric scanning mirror system. Before sample scanning, the OCT system acquires two dimensional intensity map with normalized intensity and variables in color spaces using false-color mapping. Then, the system increases or decreases reference intensity following the map data for optimization with a given algorithm. In our experiments, the proposed method successfully corrected the reference intensity with maintaining spectral shape, enabled to change integration time without manual calibration of the reference intensity, and prevented image degradation due to over-saturation and insufficient reference intensity. Also, SNR and sensitivity could be improved by increasing integration time with automatic adjustment of the reference intensity. We believe that our findings can significantly aid in the optimization of SNR and sensitivity for optical coherence tomography systems.

Image correlation method for DNA sequence alignment.

PubMed

Curilem Saldías, Millaray; Villarroel Sassarini, Felipe; Muñoz Poblete, Carlos; Vargas Vásquez, Asticio; Maureira Butler, Iván

2012-01-01

The complexity of searches and the volume of genomic data make sequence alignment one of bioinformatics most active research areas. New alignment approaches have incorporated digital signal processing techniques. Among these, correlation methods are highly sensitive. This paper proposes a novel sequence alignment method based on 2-dimensional images, where each nucleic acid base is represented as a fixed gray intensity pixel. Query and known database sequences are coded to their pixel representation and sequence alignment is handled as object recognition in a scene problem. Query and database become object and scene, respectively. An image correlation process is carried out in order to search for the best match between them. Given that this procedure can be implemented in an optical correlator, the correlation could eventually be accomplished at light speed. This paper shows an initial research stage where results were "digitally" obtained by simulating an optical correlation of DNA sequences represented as images. A total of 303 queries (variable lengths from 50 to 4500 base pairs) and 100 scenes represented by 100 x 100 images each (in total, one million base pair database) were considered for the image correlation analysis. The results showed that correlations reached very high sensitivity (99.01%), specificity (98.99%) and outperformed BLAST when mutation numbers increased. However, digital correlation processes were hundred times slower than BLAST. We are currently starting an initiative to evaluate the correlation speed process of a real experimental optical correlator. By doing this, we expect to fully exploit optical correlation light properties. As the optical correlator works jointly with the computer, digital algorithms should also be optimized. The results presented in this paper are encouraging and support the study of image correlation methods on sequence alignment.

Analysis and Implementation of Methodologies for the Monitoring of Changes in Eye Fundus Images

NASA Astrophysics Data System (ADS)

Gelroth, A.; Rodríguez, D.; Salvatelli, A.; Drozdowicz, B.; Bizai, G.

2011-12-01

We present a support system for changes detection in fundus images of the same patient taken at different time intervals. This process is useful for monitoring pathologies lasting for long periods of time, as are usually the ophthalmologic. We propose a flow of preprocessing, processing and postprocessing applied to a set of images selected from a public database, presenting pathological advances. A test interface was developed designed to select the images to be compared in order to apply the different methods developed and to display the results. We measure the system performance in terms of sensitivity, specificity and computation times. We have obtained good results, higher than 84% for the first two parameters and processing times lower than 3 seconds for 512x512 pixel images. For the specific case of detection of changes associated with bleeding, the system responds with sensitivity and specificity over 98%.

Automatic Detection of Blue-White Veil and Related Structures in Dermoscopy Images

PubMed Central

Celebi, M. Emre; Iyatomi, Hitoshi; Stoecker, William V.; Moss, Randy H.; Rabinovitz, Harold S.; Argenziano, Giuseppe; Soyer, H. Peter

2011-01-01

Dermoscopy is a non-invasive skin imaging technique, which permits visualization of features of pigmented melanocytic neoplasms that are not discernable by examination with the naked eye. One of the most important features for the diagnosis of melanoma in dermoscopy images is the blue-white veil (irregular, structureless areas of confluent blue pigmentation with an overlying white “ground-glass” film). In this article, we present a machine learning approach to the detection of blue-white veil and related structures in dermoscopy images. The method involves contextual pixel classification using a decision tree classifier. The percentage of blue-white areas detected in a lesion combined with a simple shape descriptor yielded a sensitivity of 69.35% and a specificity of 89.97% on a set of 545 dermoscopy images. The sensitivity rises to 78.20% for detection of blue veil in those cases where it is a primary feature for melanoma recognition. PMID:18804955

Elemental X-ray Imaging Using the Maia Detector Array: The Benefits and Challenges of Large Solid-Angle

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ryan, C.G.; De Geronimo, G.; Kirkham, R.

2009-11-13

The fundamental parameter method for quantitative SXRF and PIXE analysis and imaging using the dynamic analysis method is extended to model the changing X-ray yields and detector sensitivity with angle across large detector arrays. The method is implemented in the GeoPIXE software and applied to cope with the large solid-angle of the new Maia 384 detector array and its 96 detector prototype developed by CSIRO and BNL for SXRF imaging applications at the Australian and NSLS synchrotrons. Peak-to-background is controlled by mitigating charge-sharing between detectors through careful optimization of a patterned molybdenum absorber mask. A geological application demonstrates the capabilitymore » of the method to produce high definition elemental images up to {approx}100 M pixels in size.« less

In-Situ Characterization of Tissue Blood Flow, Blood Content, and Water State Using New Techniques in Magnetic Resonance Imaging.

NASA Astrophysics Data System (ADS)

Conturo, Thomas Edward

Tissue blood flow, blood content, and water state have been characterized in-situ with new nuclear magnetic resonance imaging techniques. The sensitivities of standard techniques to the physiologic tissue parameters spin density (N_{rm r}) and relaxation times (T_1 and T_2 ) are mathematically defined. A new driven inversion method is developed so that tissue T_1 and T_2 changes produce cooperative intensity changes, yielding high contrast, high signal to noise, and sensitivity to a wider range of tissue parameters. The actual tissue parameters were imaged by automated collection of multiple-echo data having multiple T _1 dependence. Data are simultaneously fit by three-parameters to a closed-form expression, producing lower inter-parameter correlation and parameter noise than in separate T_1 or T_2 methods or pre-averaged methods. Accurate parameters are obtained at different field strengths. Parametric images of pathology demonstrate high sensitivity to tissue heterogeneity, and water content is determined in many tissues. Erythrocytes were paramagnetically labeled to study blood content and relaxation mechanisms. Liver and spleen relaxation were enhanced following 10% exchange of animal blood volumes. Rapid water exchange between intracellular and extracellular compartments was validated. Erythrocytes occupied 12.5% of renal cortex volume, and blood content was uniform in the liver, spleen and kidney. The magnitude and direction of flow velocity was then imaged. To eliminate directional artifacts, a bipolar gradient technique sensitized to flow in different directions was developed. Phase angle was reconstructed instead of intensity since the former has a 2pi -fold higher dynamic range. Images of flow through curves demonstrated secondary flow with a centrifugally-biased laminar profile and stationary velocity peaks along the curvature. Portal vein flow velocities were diminished or reversed in cirrhosis. Image artifacts have been characterized and removed. The foldover in magnified images was eliminated by exciting limited regions with orthogonal pi/2 and pi pulses. Off-midline regions were imaged by tandemly offsetting the phase-encoding and excitation. Artifacts due to non-steady-state conditions were demonstrated. The approach to steady state was defined by operators and vectors, and any repeated series of RF pulses was proven to produce a steady-state. The vector difference between the magnetization and its steady state value is relatively constant during the approach. The repetition time relative to T_1 is the main determinant of approach rate, and off-resonant RF pulses incoherent with the magnetization produce a more rapid approach than on-resonant pulses.

Cell-free measurements of brightness of fluorescently labeled antibodies

PubMed Central

Zhou, Haiying; Tourkakis, George; Shi, Dennis; Kim, David M.; Zhang, Hairong; Du, Tommy; Eades, William C.; Berezin, Mikhail Y.

2017-01-01

Validation of imaging contrast agents, such as fluorescently labeled imaging antibodies, has been recognized as a critical challenge in clinical and preclinical studies. As the number of applications for imaging antibodies grows, these materials are increasingly being subjected to careful scrutiny. Antibody fluorescent brightness is one of the key parameters that is of critical importance. Direct measurements of the brightness with common spectroscopy methods are challenging, because the fluorescent properties of the imaging antibodies are highly sensitive to the methods of conjugation, degree of labeling, and contamination with free dyes. Traditional methods rely on cell-based assays that lack reproducibility and accuracy. In this manuscript, we present a novel and general approach for measuring the brightness using antibody-avid polystyrene beads and flow cytometry. As compared to a cell-based method, the described technique is rapid, quantitative, and highly reproducible. The proposed method requires less than ten microgram of sample and is applicable for optimizing synthetic conjugation procedures, testing commercial imaging antibodies, and performing high-throughput validation of conjugation procedures. PMID:28150730

The effect of different methods and image analyzers on the results of the in vivo comet assay.

PubMed

Kyoya, Takahiro; Iwamoto, Rika; Shimanura, Yuko; Terada, Megumi; Masuda, Shuichi

2018-01-01

The in vivo comet assay is a widely used genotoxicity test that can detect DNA damage in a range of organs. It is included in the Organisation for Economic Co-operation and Development Guidelines for the Testing of Chemicals. However, various protocols are still used for this assay, and several different image analyzers are used routinely to evaluate the results. Here, we verified a protocol that largely contributes to the equivalence of results, and we assessed the effect on the results when slides made from the same sample were analyzed using two different image analyzers (Comet Assay IV vs Comet Analyzer). Standardizing the agarose concentrations and DNA unwinding and electrophoresis times had a large impact on the equivalence of the results between the different methods used for the in vivo comet assay. In addition, there was some variation in the sensitivity of the two different image analyzers tested; however this variation was considered to be minor and became negligible when the test conditions were standardized between the two different methods. By standardizing the concentrations of low melting agarose and DNA unwinding and electrophoresis times between both methods used in the current study, the sensitivity to detect the genotoxicity of a positive control substance in the in vivo comet assay became generally comparable, independently of the image analyzer used. However, there may still be the possibility that other conditions, except for the three described here, could affect the reproducibility of the in vivo comet assay.

A simple optode based method for imaging O2 distribution and dynamics in tap water biofilms.

PubMed

Staal, M; Prest, E I; Vrouwenvelder, J S; Rickelt, L F; Kühl, M

2011-10-15

A ratiometric luminescence intensity imaging approach is presented, which enables spatial O2 measurements in biofilm reactors with transparent planar O2 optodes. Optodes consist of an O2 sensitive luminescent dye immobilized in a 1-10 μm thick polymeric layer on a transparent carrier, e.g. a glass window. The method is based on sequential imaging of the O2 dependent luminescence intensity, which are subsequently normalized with luminescent intensity images recorded under anoxic conditions. We present 2-dimensional O2 distribution images at the base of a tap water biofilm measured with the new ratiometric method and compare the results with O2 distribution images obtained in the same biofilm reactor with luminescence lifetime imaging. Using conventional digital cameras, such simple normalized luminescence intensity imaging can yield images of 2-dimensional O2 distributions with a high signal-to-noise ratio and spatial resolution comparable or even surpassing those obtained with expensive and complex luminescence lifetime imaging systems. The method can be applied to biofilm growth incubators allowing intermittent experimental shifts to anoxic conditions or in systems, in which the O2 concentration is depleted during incubation. Copyright © 2011 Elsevier Ltd. All rights reserved.

Label-free reflectance hyperspectral imaging for tumor margin assessment: a pilot study on surgical specimens of cancer patients

NASA Astrophysics Data System (ADS)

Fei, Baowei; Lu, Guolan; Wang, Xu; Zhang, Hongzheng; Little, James V.; Patel, Mihir R.; Griffith, Christopher C.; El-Diery, Mark W.; Chen, Amy Y.

2017-08-01

A label-free, hyperspectral imaging (HSI) approach has been proposed for tumor margin assessment. HSI data, i.e., hypercube (x,y,λ), consist of a series of high-resolution images of the same field of view that are acquired at different wavelengths. Every pixel on an HSI image has an optical spectrum. In this pilot clinical study, a pipeline of a machine-learning-based quantification method for HSI data was implemented and evaluated in patient specimens. Spectral features from HSI data were used for the classification of cancer and normal tissue. Surgical tissue specimens were collected from 16 human patients who underwent head and neck (H&N) cancer surgery. HSI, autofluorescence images, and fluorescence images with 2-deoxy-2-[(7-nitro-2,1,3-benzoxadiazol-4-yl)amino]-D-glucose (2-NBDG) and proflavine were acquired from each specimen. Digitized histologic slides were examined by an H&N pathologist. The HSI and classification method were able to distinguish between cancer and normal tissue from the oral cavity with an average accuracy of 90%±8%, sensitivity of 89%±9%, and specificity of 91%±6%. For tissue specimens from the thyroid, the method achieved an average accuracy of 94%±6%, sensitivity of 94%±6%, and specificity of 95%±6%. HSI outperformed autofluorescence imaging or fluorescence imaging with vital dye (2-NBDG or proflavine). This study demonstrated the feasibility of label-free, HSI for tumor margin assessment in surgical tissue specimens of H&N cancer patients. Further development of the HSI technology is warranted for its application in image-guided surgery.

Coupled multiview autoencoders with locality sensitivity for three-dimensional human pose estimation

NASA Astrophysics Data System (ADS)

Yu, Jialin; Sun, Jifeng; Luo, Shasha; Duan, Bichao

2017-09-01

Estimating three-dimensional (3D) human poses from a single camera is usually implemented by searching pose candidates with image descriptors. Existing methods usually suppose that the mapping from feature space to pose space is linear, but in fact, their mapping relationship is highly nonlinear, which heavily degrades the performance of 3D pose estimation. We propose a method to recover 3D pose from a silhouette image. It is based on the multiview feature embedding (MFE) and the locality-sensitive autoencoders (LSAEs). On the one hand, we first depict the manifold regularized sparse low-rank approximation for MFE and then the input image is characterized by a fused feature descriptor. On the other hand, both the fused feature and its corresponding 3D pose are separately encoded by LSAEs. A two-layer back-propagation neural network is trained by parameter fine-tuning and then used to map the encoded 2D features to encoded 3D poses. Our LSAE ensures a good preservation of the local topology of data points. Experimental results demonstrate the effectiveness of our proposed method.

Recent Developments in VSD Imaging of Small Neuronal Networks

ERIC Educational Resources Information Center

Hill, Evan S.; Bruno, Angela M.; Frost, William N.

2014-01-01

Voltage-sensitive dye (VSD) imaging is a powerful technique that can provide, in single experiments, a large-scale view of network activity unobtainable with traditional sharp electrode recording methods. Here we review recent work using VSDs to study small networks and highlight several results from this approach. Topics covered include circuit…

Seeing the Invisible with Schlieren Imaging

ERIC Educational Resources Information Center

Lekholm, Ville; Ramme, Goran; Thornell, Greger

2011-01-01

Schlieren imaging is a method for visualizing differences in refractive index as caused by pressure or temperature non-uniformities within a medium, or as caused by the mixing of two fluids. It is an inexpensive yet powerful and straightforward tool for sensitive and high-resolution visualization of otherwise invisible phenomena. In this article,…

A novel algorithm for thermal image encryption.

PubMed

Hussain, Iqtadar; Anees, Amir; Algarni, Abdulmohsen

2018-04-16

Thermal images play a vital character at nuclear plants, Power stations, Forensic labs biological research, and petroleum products extraction. Safety of thermal images is very important. Image data has some unique features such as intensity, contrast, homogeneity, entropy and correlation among pixels that is why somehow image encryption is trickier as compare to other encryptions. With conventional image encryption schemes it is normally hard to handle these features. Therefore, cryptographers have paid attention to some attractive properties of the chaotic maps such as randomness and sensitivity to build up novel cryptosystems. That is why, recently proposed image encryption techniques progressively more depends on the application of chaotic maps. This paper proposed an image encryption algorithm based on Chebyshev chaotic map and S8 Symmetric group of permutation based substitution boxes. Primarily, parameters of chaotic Chebyshev map are chosen as a secret key to mystify the primary image. Then, the plaintext image is encrypted by the method generated from the substitution boxes and Chebyshev map. By this process, we can get a cipher text image that is perfectly twisted and dispersed. The outcomes of renowned experiments, key sensitivity tests and statistical analysis confirm that the proposed algorithm offers a safe and efficient approach for real-time image encryption.

Flexible Measurement of Bioluminescent Reporters Using an Automated Longitudinal Luciferase Imaging Gas- and Temperature-optimized Recorder (ALLIGATOR).

PubMed

Crosby, Priya; Hoyle, Nathaniel P; O'Neill, John S

2017-12-13

Luciferase-based reporters of cellular gene expression are in widespread use for both longitudinal and end-point assays of biological activity. In circadian rhythms research, for example, clock gene fusions with firefly luciferase give rise to robust rhythms in cellular bioluminescence that persist over many days. Technical limitations associated with photomultiplier tubes (PMT) or conventional microscopy-based methods for bioluminescence quantification have typically demanded that cells and tissues be maintained under quite non-physiological conditions during recording, with a trade-off between sensitivity and throughput. Here, we report a refinement of prior methods that allows long-term bioluminescence imaging with high sensitivity and throughput which supports a broad range of culture conditions, including variable gas and humidity control, and that accepts many different tissue culture plates and dishes. This automated longitudinal luciferase imaging gas- and temperature-optimized recorder (ALLIGATOR) also allows the observation of spatial variations in luciferase expression across a cell monolayer or tissue, which cannot readily be observed by traditional methods. We highlight how the ALLIGATOR provides vastly increased flexibility for the detection of luciferase activity when compared with existing methods.

A Method for Rapid Measurement of Contrast Sensitivity on Mobile Touch-Screens

NASA Technical Reports Server (NTRS)

Mulligan, Jeffrey B.

2016-01-01

Touch-screen displays in cell phones and tablet computers are now pervasive, making them an attractive option for vision testing outside of the laboratory or clinic. Here we de- scribe a novel method in which subjects use a finger swipe to indicate the transition from visible to invisible on a grating which is swept in both contrast and frequency. Because a single image can be swiped in about a second, it is practical to use a series of images to zoom in on particular ranges of contrast or frequency, both to increase the accuracy of the measurements and to obtain an estimate of the reliability of the subject. Sensitivities to chromatic and spatio-temporal modulations are easily measured using the same method. A proto- type has been developed for Apple Computer's iPad/iPod/iPhone family of devices, implemented using an open-source scripting environment known as QuIP (QUick Image Processing, http://hsi.arc.nasa.gov/groups/scanpath/research.php). Preliminary data show good agreement with estimates obtained from traditional psychophysical methods as well as newer rapid estimation techniques. Issues relating to device calibration are also discussed.

Holographic deep learning for rapid optical screening of anthrax spores

PubMed Central

Jo, YoungJu; Park, Sangjin; Jung, JaeHwang; Yoon, Jonghee; Joo, Hosung; Kim, Min-hyeok; Kang, Suk-Jo; Choi, Myung Chul; Lee, Sang Yup; Park, YongKeun

2017-01-01

Establishing early warning systems for anthrax attacks is crucial in biodefense. Despite numerous studies for decades, the limited sensitivity of conventional biochemical methods essentially requires preprocessing steps and thus has limitations to be used in realistic settings of biological warfare. We present an optical method for rapid and label-free screening of Bacillus anthracis spores through the synergistic application of holographic microscopy and deep learning. A deep convolutional neural network is designed to classify holographic images of unlabeled living cells. After training, the network outperforms previous techniques in all accuracy measures, achieving single-spore sensitivity and subgenus specificity. The unique “representation learning” capability of deep learning enables direct training from raw images instead of manually extracted features. The method automatically recognizes key biological traits encoded in the images and exploits them as fingerprints. This remarkable learning ability makes the proposed method readily applicable to classifying various single cells in addition to B. anthracis, as demonstrated for the diagnosis of Listeria monocytogenes, without any modification. We believe that our strategy will make holographic microscopy more accessible to medical doctors and biomedical scientists for easy, rapid, and accurate point-of-care diagnosis of pathogens. PMID:28798957

Iodine-123 metaiodobenzylguanidine scintigraphy and iodine-123 ioflupane single photon emission computed tomography in Lewy body diseases: complementary or alternative techniques?

PubMed

Treglia, Giorgio; Cason, Ernesto; Cortelli, Pietro; Gabellini, Anna; Liguori, Rocco; Bagnato, Antonio; Giordano, Alessandro; Fagioli, Giorgio

2014-01-01

To compare myocardial sympathetic imaging using (123)I-Metaiodobenzylguanidine (MIBG) scintigraphy and striatal dopaminergic imaging using (123)I-Ioflupane (FP-CIT) single photon emission computed tomography (SPECT) in patients with suspected Lewy body diseases (LBD). Ninety-nine patients who performed both methods within 2 months for differential diagnosis between Parkinson's disease (PD) and other parkinsonism (n = 68) or between dementia with Lewy bodies (DLB) and other dementia (n = 31) were enrolled. Sensitivity, specificity, accuracy, positive and negative predictive values of both methods were calculated. For (123) I-MIBG scintigraphy, the overall sensitivity, specificity, accuracy, positive and negative predictive values in LBD were 83%, 79%, 82%, 86%, and 76%, respectively. For (123)I-FP-CIT SPECT, the overall sensitivity, specificity, accuracy, positive and negative predictive values in LBD were 93%, 41%, 73%, 71%, and 80%, respectively. There was a statistically significant difference between these two methods in patients without LBD, but not in patients with LBD. LBD usually present both myocardial sympathetic and striatal dopaminergic impairments. (123)I-FP-CIT SPECT presents high sensitivity in the diagnosis of LBD; (123)I-MIBG scintigraphy may have a complementary role in differential diagnosis between PD and other parkinsonism. These scintigraphic methods showed similar diagnostic accuracy in differential diagnosis between DLB and other dementia. Copyright © 2012 by the American Society of Neuroimaging.

Ultra-sensitive chemiluminescence imaging DNA hybridization method in the detection of mosquito-borne viruses and parasites.

PubMed

Zhang, Yingjie; Liu, Qiqi; Zhou, Biao; Wang, Xiaobo; Chen, Suhong; Wang, Shengqi

2017-01-25

Mosquito-borne viruses (MBVs) and parasites (MBPs) are transmitted through hematophagous arthropods-mosquitoes to homoiothermous vertebrates. This study aims at developing a detection method to monitor the spread of mosquito-borne diseases to new areas and diagnose the infections caused by MBVs and MBPs. In this assay, an ultra-sensitive chemiluminescence (CL) detection method was developed and used to simultaneously detect 19 common MBVs and MBPs. In vitro transcript RNA, virus-like particles (VLPs), and plasmids were established as positive or limit of detection (LOD) reference materials. MBVs and MBPs could be genotyped with high sensitivity and specificity. The cut-off values of probes were calculated. The absolute LODs of this strategy to detect serially diluted in vitro transcribed RNAs of MBVs and serially diluted plasmids of MBPs were 10 2 -10 3 copies/μl and 10 1 -10 2 copies/μl, respectively. Further, the LOD of detecting a strain of pre-quantified JEV was 10 1.8 -10 0.8 PFU/ml, fitted well in a linear regression model (coefficient of determination = 0.9678). Ultra-sensitive CL imaging DNA hybridization was developed and could simultaneously detect various MBVs and MBPs. The method described here has the potential to provide considerable labor savings due to its ability to screen for 19 mosquito-borne pathogens simultaneously.

Measuring noise equivalent irradiance of a digital short-wave infrared imaging system using a broadband source to simulate the night spectrum

NASA Astrophysics Data System (ADS)

Green, John R.; Robinson, Timothy

2015-05-01

There is a growing interest in developing helmet-mounted digital imaging systems (HMDIS) for integration into military aircraft cockpits. This interest stems from the multiple advantages of digital vs. analog imaging such as image fusion from multiple sensors, data processing to enhance the image contrast, superposition of non-imaging data over the image, and sending images to remote location for analysis. There are several properties an HMDIS must have in order to aid the pilot during night operations. In addition to the resolution, image refresh rate, dynamic range, and sensor uniformity over the entire Focal Plane Array (FPA); the imaging system must have the sensitivity to detect the limited night light available filtered through cockpit transparencies. Digital sensor sensitivity is generally measured monochromatically using a laser with a wavelength near the peak detector quantum efficiency, and is generally reported as either the Noise Equivalent Power (NEP) or Noise Equivalent Irradiance (NEI). This paper proposes a test system that measures NEI of Short-Wave Infrared (SWIR) digital imaging systems using a broadband source that simulates the night spectrum. This method has a few advantages over a monochromatic method. Namely, the test conditions provide spectrum closer to what is experienced by the end-user, and the resulting NEI may be compared directly to modeled night glow irradiance calculation. This comparison may be used to assess the Technology Readiness Level of the imaging system for the application. The test system is being developed under a Cooperative Research and Development Agreement (CRADA) with the Air Force Research Laboratory.

Automated pathologies detection in retina digital images based on complex continuous wavelet transform phase angles.

PubMed

Lahmiri, Salim; Gargour, Christian S; Gabrea, Marcel

2014-10-01

An automated diagnosis system that uses complex continuous wavelet transform (CWT) to process retina digital images and support vector machines (SVMs) for classification purposes is presented. In particular, each retina image is transformed into two one-dimensional signals by concatenating image rows and columns separately. The mathematical norm of phase angles found in each one-dimensional signal at each level of CWT decomposition are relied on to characterise the texture of normal images against abnormal images affected by exudates, drusen and microaneurysms. The leave-one-out cross-validation method was adopted to conduct experiments and the results from the SVM show that the proposed approach gives better results than those obtained by other methods based on the correct classification rate, sensitivity and specificity.

Characterization of an intraluminal differential frequency-domain photoacoustics system

NASA Astrophysics Data System (ADS)

Lashkari, Bahman; Son, Jungik; Liang, Simon; Castelino, Robin; Foster, F. Stuart; Courtney, Brian; Mandelis, Andreas

2016-03-01

Cardiovascular related diseases are ranked as the second highest cause of death in Canada. Among the most important cardiovascular diseases is atherosclerosis. Current methods of diagnosis of atherosclerosis consist of angiography, intravascular ultrasound (IVUS) and optical coherence tomography (OCT). None of these methods possesses adequate sensitivity, as the ideal technique should be capable of both depth profiling, as well as functional imaging. An alternative technique is photoacoustics (PA) which can perform deep imaging and spectroscopy. The presented study explores the application of wavelength-modulated differential photoacoustic radar (WM-DPAR) for characterizing arterial vessels. The wavelength-modulated differential photoacoustic technique was shown to be able to substantially increase the dynamic range and sensitivity of hemoglobin oxygenation level detection. In this work the differential PA technique was used with a very high frequency modulation range. To perform spectroscopic PA imaging, at least two wavelengths are required. The selected wavelengths for this work are 1210 nm and 980 nm. 1210 nm corresponds to the maximum optical absorption coefficient of cholesterol and cholesteryl esters which are the main constituents of plaques. Since water, elastin and collagen also have high absorption coefficients at 1210 nm, this wavelength alone cannot provide very high sensitivity and specificity. The additional wavelength, 980 nm corresponds to high absorption coefficient of those constituents of healthy artery tissue. The simultaneous application of the abovementioned wavelengths can provide higher sensitivity and improved specificity in detecting lipids in the arterial vessels.

Distributed Kernelized Locality-Sensitive Hashing for Faster Image Based Navigation

DTIC Science & Technology

2015-03-26

Facebook, Google, and Yahoo !. Current methods for image retrieval become problematic when implemented on image datasets that can easily reach billions of...correlations. Tech industry leaders like Facebook, Google, and Yahoo ! sort and index even larger volumes of “big data” daily. When attempting to process...open source implementation of Google’s MapReduce programming paradigm [13] which has been used for many different things. Using Apache Hadoop, Yahoo

A new axial smoothing method based on elastic mapping

NASA Astrophysics Data System (ADS)

Yang, J.; Huang, S. C.; Lin, K. P.; Czernin, J.; Wolfenden, P.; Dahlbom, M.; Hoh, C. K.; Phelps, M. E.

1996-12-01

New positron emission tomography (PET) scanners have higher axial and in-plane spatial resolutions but at the expense of reduced per plane sensitivity, which prevents the higher resolution from being fully realized. Normally, Gaussian-weighted interplane axial smoothing is used to reduce noise. In this study, the authors developed a new algorithm that first elastically maps adjacent planes, and then the mapped images are smoothed axially to reduce the image noise level. Compared to those obtained by the conventional axial-directional smoothing method, the images by the new method have improved signal-to-noise ratio. To quantify the signal-to-noise improvement, both simulated and real cardiac PET images were studied. Various Hanning reconstruction filters with cutoff frequency=0.5, 0.7, 1.0/spl times/Nyquist frequency and Ramp filter were tested on simulated images. Effective in-plane resolution was measured by the effective global Gaussian resolution (EGGR) and noise reduction was evaluated by the cross-correlation coefficient. Results showed that the new method was robust to various noise levels and indicated larger noise reduction or better image feature preservation (i.e., smaller EGGR) than by the conventional method.

Optical image encryption by random shifting in fractional Fourier domains

NASA Astrophysics Data System (ADS)

Hennelly, B.; Sheridan, J. T.

2003-02-01

A number of methods have recently been proposed in the literature for the encryption of two-dimensional information by use of optical systems based on the fractional Fourier transform. Typically, these methods require random phase screen keys for decrypting the data, which must be stored at the receiver and must be carefully aligned with the received encrypted data. A new technique based on a random shifting, or jigsaw, algorithm is proposed. This method does not require the use of phase keys. The image is encrypted by juxtaposition of sections of the image in fractional Fourier domains. The new method has been compared with existing methods and shows comparable or superior robustness to blind decryption. Optical implementation is discussed, and the sensitivity of the various encryption keys to blind decryption is examined.

Novel techniques for enhancement and segmentation of acne vulgaris lesions.

PubMed

Malik, A S; Humayun, J; Kamel, N; Yap, F B-B

2014-08-01

More than 99% acne patients suffer from acne vulgaris. While diagnosing the severity of acne vulgaris lesions, dermatologists have observed inter-rater and intra-rater variability in diagnosis results. This is because during assessment, identifying lesion types and their counting is a tedious job for dermatologists. To make the assessment job objective and easier for dermatologists, an automated system based on image processing methods is proposed in this study. There are two main objectives: (i) to develop an algorithm for the enhancement of various acne vulgaris lesions; and (ii) to develop a method for the segmentation of enhanced acne vulgaris lesions. For the first objective, an algorithm is developed based on the theory of high dynamic range (HDR) images. The proposed algorithm uses local rank transform to generate the HDR images from a single acne image followed by the log transformation. Then, segmentation is performed by clustering the pixels based on Mahalanobis distance of each pixel from spectral models of acne vulgaris lesions. Two metrics are used to evaluate the enhancement of acne vulgaris lesions, i.e., contrast improvement factor (CIF) and image contrast normalization (ICN). The proposed algorithm is compared with two other methods. The proposed enhancement algorithm shows better result than both the other methods based on CIF and ICN. In addition, sensitivity and specificity are calculated for the segmentation results. The proposed segmentation method shows higher sensitivity and specificity than other methods. This article specifically discusses the contrast enhancement and segmentation for automated diagnosis system of acne vulgaris lesions. The results are promising that can be used for further classification of acne vulgaris lesions for final grading of the lesions. © 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

A simple and effective radiometric correction method to improve landscape change detection across sensors and across time

USGS Publications Warehouse

Chen, X.; Vierling, Lee; Deering, D.

2005-01-01

Satellite data offer unrivaled utility in monitoring and quantifying large scale land cover change over time. Radiometric consistency among collocated multi-temporal imagery is difficult to maintain, however, due to variations in sensor characteristics, atmospheric conditions, solar angle, and sensor view angle that can obscure surface change detection. To detect accurate landscape change using multi-temporal images, we developed a variation of the pseudoinvariant feature (PIF) normalization scheme: the temporally invariant cluster (TIC) method. Image data were acquired on June 9, 1990 (Landsat 4), June 20, 2000 (Landsat 7), and August 26, 2001 (Landsat 7) to analyze boreal forests near the Siberian city of Krasnoyarsk using the normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), and reduced simple ratio (RSR). The temporally invariant cluster (TIC) centers were identified via a point density map of collocated pixel VIs from the base image and the target image, and a normalization regression line was created to intersect all TIC centers. Target image VI values were then recalculated using the regression function so that these two images could be compared using the resulting common radiometric scale. We found that EVI was very indicative of vegetation structure because of its sensitivity to shadowing effects and could thus be used to separate conifer forests from deciduous forests and grass/crop lands. Conversely, because NDVI reduced the radiometric influence of shadow, it did not allow for distinctions among these vegetation types. After normalization, correlations of NDVI and EVI with forest leaf area index (LAI) field measurements combined for 2000 and 2001 were significantly improved; the r 2 values in these regressions rose from 0.49 to 0.69 and from 0.46 to 0.61, respectively. An EVI "cancellation effect" where EVI was positively related to understory greenness but negatively related to forest canopy coverage was evident across a post fire chronosequence with normalized data. These findings indicate that the TIC method provides a simple, effective and repeatable method to create radiometrically comparable data sets for remote detection of landscape change. Compared to some previous relative radiometric normalization methods, this new method does not require high level programming and statistical skills, yet remains sensitive to landscape changes occurring over seasonal and inter-annual time scales. In addition, the TIC method maintains sensitivity to subtle changes in vegetation phenology and enables normalization even when invariant features are rare. While this normalization method allowed detection of a range of land use, land cover, and phenological/biophysical changes in the Siberian boreal forest region studied here, it is necessary to further examine images representing a wide variety of ecoregions to thoroughly evaluate the TIC method against other normalization schemes. ?? 2005 Elsevier Inc. All rights reserved.

Detection of brain tumor margins using optical coherence tomography

NASA Astrophysics Data System (ADS)

Juarez-Chambi, Ronald M.; Kut, Carmen; Rico-Jimenez, Jesus; Campos-Delgado, Daniel U.; Quinones-Hinojosa, Alfredo; Li, Xingde; Jo, Javier

2018-02-01

In brain cancer surgery, it is critical to achieve extensive resection without compromising adjacent healthy, noncancerous regions. Various technological advances have made major contributions in imaging, including intraoperative magnetic imaging (MRI) and computed tomography (CT). However, these technologies have pros and cons in providing quantitative, real-time and three-dimensional (3D) continuous guidance in brain cancer detection. Optical Coherence Tomography (OCT) is a non-invasive, label-free, cost-effective technique capable of imaging tissue in three dimensions and real time. The purpose of this study is to reliably and efficiently discriminate between non-cancer and cancerinfiltrated brain regions using OCT images. To this end, a mathematical model for quantitative evaluation known as the Blind End-Member and Abundances Extraction method (BEAE). This BEAE method is a constrained optimization technique which extracts spatial information from volumetric OCT images. Using this novel method, we are able to discriminate between cancerous and non-cancerous tissues and using logistic regression as a classifier for automatic brain tumor margin detection. Using this technique, we are able to achieve excellent performance using an extensive cross-validation of the training dataset (sensitivity 92.91% and specificity 98.15%) and again using an independent, blinded validation dataset (sensitivity 92.91% and specificity 86.36%). In summary, BEAE is well-suited to differentiate brain tissue which could support the guiding surgery process for tissue resection.

Detection of brain tumor margins using optical coherence tomography

NASA Astrophysics Data System (ADS)

Juarez-Chambi, Ronald M.; Kut, Carmen; Rico-Jimenez, Jesus; Campos-Delgado, Daniel U.; Quinones-Hinojosa, Alfredo; Li, Xingde; Jo, Javier

2018-02-01

In brain cancer surgery, it is critical to achieve extensive resection without compromising adjacent healthy, non-cancerous regions. Various technological advances have made major contributions in imaging, including intraoperative magnetic imaging (MRI) and computed tomography (CT). However, these technologies have pros and cons in providing quantitative, real-time and three-dimensional (3D) continuous guidance in brain cancer detection. Optical Coherence Tomography (OCT) is a non-invasive, label-free, cost-effective technique capable of imaging tissue in three dimensions and real time. The purpose of this study is to reliably and efficiently discriminate between non-cancer and cancer-infiltrated brain regions using OCT images. To this end, a mathematical model for quantitative evaluation known as the Blind End- Member and Abundances Extraction method (BEAE). This BEAE method is a constrained optimization technique which extracts spatial information from volumetric OCT images. Using this novel method, we are able to discriminate between cancerous and non-cancerous tissues and using logistic regression as a classifier for automatic brain tumor margin detection. Using this technique, we are able to achieve excellent performance using an extensive cross-validation of the training dataset (sensitivity 92.91% and specificity 98.15%) and again using an independent, blinded validation dataset (sensitivity 92.91% and specificity 86.36%). In summary, BEAE is well-suited to differentiate brain tissue which could support the guiding surgery process for tissue resection.

Reconstruction of dynamic image series from undersampled MRI data using data-driven model consistency condition (MOCCO).

PubMed

Velikina, Julia V; Samsonov, Alexey A

2015-11-01

To accelerate dynamic MR imaging through development of a novel image reconstruction technique using low-rank temporal signal models preestimated from training data. We introduce the model consistency condition (MOCCO) technique, which utilizes temporal models to regularize reconstruction without constraining the solution to be low-rank, as is performed in related techniques. This is achieved by using a data-driven model to design a transform for compressed sensing-type regularization. The enforcement of general compliance with the model without excessively penalizing deviating signal allows recovery of a full-rank solution. Our method was compared with a standard low-rank approach utilizing model-based dimensionality reduction in phantoms and patient examinations for time-resolved contrast-enhanced angiography (CE-MRA) and cardiac CINE imaging. We studied the sensitivity of all methods to rank reduction and temporal subspace modeling errors. MOCCO demonstrated reduced sensitivity to modeling errors compared with the standard approach. Full-rank MOCCO solutions showed significantly improved preservation of temporal fidelity and aliasing/noise suppression in highly accelerated CE-MRA (acceleration up to 27) and cardiac CINE (acceleration up to 15) data. MOCCO overcomes several important deficiencies of previously proposed methods based on pre-estimated temporal models and allows high quality image restoration from highly undersampled CE-MRA and cardiac CINE data. © 2014 Wiley Periodicals, Inc.

Tracking single membrane targets of human autoantibodies using single nanoparticle imaging.

PubMed

Jézéquel, Julie; Dupuis, Julien P; Maingret, François; Groc, Laurent

2018-04-21

Over the past decade, an increasing number of neurological and neuropsychiatric diseases have been associated with the expression of autoantibodies directed against neuronal targets, including neurotransmitter receptors. Although cell-based assays are routinely used in clinics to detect the presence of immunoglobulins, such tests often provide heterogeneous outcomes due to their limited sensitivity, especially at low titers. Thus, there is an urging need for new methods allowing the detection of autoantibodies in seropositive patients that cannot always be clinically distinguished from seronegative ones. Here we make a case for single nanoparticle imaging approaches as a highly sensitive antibody detection assay. Through high-affinity interactions between functionalized nanoparticles and autoantibodies that recognize extracellular domains of membrane neuronal targets, single nanoparticle imaging allows a live surface staining of transmembrane proteins and gives access to their surface dynamics. We show here that this method is well-suited to detect low titers of purified immunoglobulin G (IgG) from first-episode psychotic patients and demonstrate that these IgG target glutamatergic N-Methyl-d-Aspartate receptors (NMDAR) in live hippocampal neurons. The molecular behaviors of targeted membrane receptors were indistinguishable from those of endogenous GluN1 NMDAR subunit and were virtually independent of the IgG concentration present in the sample contrary to classical cell-based assays. Single nanoparticle imaging emerges as a real-time sensitive method to detect IgG directed against neuronal surface proteins, which could be used as an additional step to rule out ambiguous seropositivity diagnoses. Copyright © 2018 Elsevier B.V. All rights reserved.

In-Vivo Imaging of Cell Migration Using Contrast Enhanced MRI and SVM Based Post-Processing.

PubMed

Weis, Christian; Hess, Andreas; Budinsky, Lubos; Fabry, Ben

2015-01-01

The migration of cells within a living organism can be observed with magnetic resonance imaging (MRI) in combination with iron oxide nanoparticles as an intracellular contrast agent. This method, however, suffers from low sensitivity and specificty. Here, we developed a quantitative non-invasive in-vivo cell localization method using contrast enhanced multiparametric MRI and support vector machines (SVM) based post-processing. Imaging phantoms consisting of agarose with compartments containing different concentrations of cancer cells labeled with iron oxide nanoparticles were used to train and evaluate the SVM for cell localization. From the magnitude and phase data acquired with a series of T2*-weighted gradient-echo scans at different echo-times, we extracted features that are characteristic for the presence of superparamagnetic nanoparticles, in particular hyper- and hypointensities, relaxation rates, short-range phase perturbations, and perturbation dynamics. High detection quality was achieved by SVM analysis of the multiparametric feature-space. The in-vivo applicability was validated in animal studies. The SVM detected the presence of iron oxide nanoparticles in the imaging phantoms with high specificity and sensitivity with a detection limit of 30 labeled cells per mm3, corresponding to 19 μM of iron oxide. As proof-of-concept, we applied the method to follow the migration of labeled cancer cells injected in rats. The combination of iron oxide labeled cells, multiparametric MRI and a SVM based post processing provides high spatial resolution, specificity, and sensitivity, and is therefore suitable for non-invasive in-vivo cell detection and cell migration studies over prolonged time periods.

SISGR: Room Temperature Single-Molecule Detection and Imaging by Stimulated Emission Microscopy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xie, Xiaoliang Sunney

Single-molecule spectroscopy has made considerable impact on many disciplines including chemistry, physics, and biology. To date, most single-molecule spectroscopy work is accomplished by detecting fluorescence. On the other hand, many naturally occurring chromophores, such as retinal, hemoglobin and cytochromes, do not have detectable fluorescence. There is an emerging need for single-molecule spectroscopy techniques that do not require fluorescence. In the last proposal period, we have successfully demonstrated stimulated emission microscopy, single molecule absorption, and stimulated Raman microscopy based on a high-frequency modulation transfer technique. These first-of-a- kind new spectroscopy/microscopy methods tremendously improved our ability to observe molecules that fluorescence weakly,more » even to the limit of single molecule detection for absorption measurement. All of these methods employ two laser beams: one (pump beam) excites a single molecule to a real or virtual excited state, and the other (probe beam) monitors the absorption/emission property of the single. We extract the intensity change of the probe beam with high sensitivity by implementing a high-frequency phase-sensitive detection scheme, which offers orders of magnitude improvement in detection sensitivity over direct absorption/emission measurement. However, single molecule detection based on fluorescence or absorption is fundamentally limited due to their broad spectral response. It is important to explore other avenues in single molecule detection and imaging which provides higher molecular specificity for studying a wide variety of heterogeneous chemical and biological systems. This proposal aimed to achieve single-molecule detection sensitivity with near resonance stimulated Raman scattering (SRS) microscopy. SRS microscopy was developed in our lab as a powerful technique for imaging heterogeneous samples based on their intrinsic vibrational contrasts, which provides much higher molecular specificity than absorption and fluorescence. Current sensitivity limit of SRS microscopy has not yet reached single molecule detection. We proposed to capitalize on our state-of-the-art SRS microscopy and develop near-resonance enhanced SRS for single molecule detection of carotenoids and heme proteins. The specific aims we pursued are: (1) building the next SRS generation microscope that utilizes near resonance enhancement to allow detection and imaging of single molecules with undetectable fluorescence, such as -carotene. (2) using near-resonance SRS as a contrast mechanism to study dye-sensitize semiconductor interface, elucidating the heterogeneous electron ejection kinetics with high spatial and temporal resolution. (3) studying the binding and unbinding of oxygen in single hemoglobin molecules in order to gain molecular level understanding of the long-standing issue of cooperativity. The new methods developed in the fund period of this grant have advanced the detection sensitivity in many aspects. Near-resonance SRS improved the signal by using shorter wavelengths for SRS microscopy. Frequency modulation and multi-color SRS target the reduction of background to improve the chemical specificity of SRS while maintaining the high imaging speed. Time-domain coherent Raman scattering microscopy targets to reduce the noise floor of coherent Raman microscopy. These methods have already demonstrated first-of-a-kind new applications in biology and medical research. However, we are still one order of magnitude away from single molecule limit. It is important to continue to improve the laser specification and develop new imaging methods to finally achieve label-free single molecule microscopy.« less

Detection of immunocytological markers in photomicroscopic images

NASA Astrophysics Data System (ADS)

Friedrich, David; zur Jacobsmühlen, Joschka; Braunschweig, Till; Bell, André; Chaisaowong, Kraisorn; Knüchel-Clarke, Ruth; Aach, Til

2012-03-01

Early detection of cervical cancer can be achieved through visual analysis of cell anomalies. The established PAP smear achieves a sensitivity of 50-90%, most false negative results are caused by mistakes in the preparation of the specimen or reader variability in the subjective, visual investigation. Since cervical cancer is caused by human papillomavirus (HPV), the detection of HPV-infected cells opens new perspectives for screening of precancerous abnormalities. Immunocytochemical preparation marks HPV-positive cells in brush smears of the cervix with high sensitivity and specificity. The goal of this work is the automated detection of all marker-positive cells in microscopic images of a sample slide stained with an immunocytochemical marker. A color separation technique is used to estimate the concentrations of the immunocytochemical marker stain as well as of the counterstain used to color the nuclei. Segmentation methods based on Otsu's threshold selection method and Mean Shift are adapted to the task of segmenting marker-positive cells and their nuclei. The best detection performance of single marker-positive cells was achieved with the adapted thresholding method with a sensitivity of 95.9%. The contours differed by a modified Hausdorff Distance (MHD) of 2.8 μm. Nuclei of single marker positive cells were detected with a sensitivity of 95.9% and MHD = 1.02 μm.

Functional magnetic resonance imaging activation detection: fuzzy cluster analysis in wavelet and multiwavelet domains.

PubMed

Jahanian, Hesamoddin; Soltanian-Zadeh, Hamid; Hossein-Zadeh, Gholam-Ali

2005-09-01

To present novel feature spaces, based on multiscale decompositions obtained by scalar wavelet and multiwavelet transforms, to remedy problems associated with high dimension of functional magnetic resonance imaging (fMRI) time series (when they are used directly in clustering algorithms) and their poor signal-to-noise ratio (SNR) that limits accurate classification of fMRI time series according to their activation contents. Using randomization, the proposed method finds wavelet/multiwavelet coefficients that represent the activation content of fMRI time series and combines them to define new feature spaces. Using simulated and experimental fMRI data sets, the proposed feature spaces are compared to the cross-correlation (CC) feature space and their performances are evaluated. In these studies, the false positive detection rate is controlled using randomization. To compare different methods, several points of the receiver operating characteristics (ROC) curves, using simulated data, are estimated and compared. The proposed features suppress the effects of confounding signals and improve activation detection sensitivity. Experimental results show improved sensitivity and robustness of the proposed method compared to the conventional CC analysis. More accurate and sensitive activation detection can be achieved using the proposed feature spaces compared to CC feature space. Multiwavelet features show superior detection sensitivity compared to the scalar wavelet features. (c) 2005 Wiley-Liss, Inc.

Brightness-preserving fuzzy contrast enhancement scheme for the detection and classification of diabetic retinopathy disease.

PubMed

Datta, Niladri Sekhar; Dutta, Himadri Sekhar; Majumder, Koushik

2016-01-01

The contrast enhancement of retinal image plays a vital role for the detection of microaneurysms (MAs), which are an early sign of diabetic retinopathy disease. A retinal image contrast enhancement method has been presented to improve the MA detection technique. The success rate on low-contrast noisy retinal image analysis shows the importance of the proposed method. Overall, 587 retinal input images are tested for performance analysis. The average sensitivity and specificity are obtained as 95.94% and 99.21%, respectively. The area under curve is found as 0.932 for the receiver operating characteristics analysis. The classifications of diabetic retinopathy disease are also performed here. The experimental results show that the overall MA detection method performs better than the current state-of-the-art MA detection algorithms.

Video compression of coronary angiograms based on discrete wavelet transform with block classification.

PubMed

Ho, B T; Tsai, M J; Wei, J; Ma, M; Saipetch, P

1996-01-01

A new method of video compression for angiographic images has been developed to achieve high compression ratio (~20:1) while eliminating block artifacts which leads to loss of diagnostic accuracy. This method adopts motion picture experts group's (MPEGs) motion compensated prediction to takes advantage of frame to frame correlation. However, in contrast to MPEG, the error images arising from mismatches in the motion estimation are encoded by discrete wavelet transform (DWT) rather than block discrete cosine transform (DCT). Furthermore, the authors developed a classification scheme which label each block in an image as intra, error, or background type and encode it accordingly. This hybrid coding can significantly improve the compression efficiency in certain eases. This method can be generalized for any dynamic image sequences applications sensitive to block artifacts.

Evaluation Methodology between Globalization and Localization Features Approaches for Skin Cancer Lesions Classification

NASA Astrophysics Data System (ADS)

Ahmed, H. M.; Al-azawi, R. J.; Abdulhameed, A. A.

2018-05-01

Huge efforts have been put in the developing of diagnostic methods to skin cancer disease. In this paper, two different approaches have been addressed for detection the skin cancer in dermoscopy images. The first approach uses a global method that uses global features for classifying skin lesions, whereas the second approach uses a local method that uses local features for classifying skin lesions. The aim of this paper is selecting the best approach for skin lesion classification. The dataset has been used in this paper consist of 200 dermoscopy images from Pedro Hispano Hospital (PH2). The achieved results are; sensitivity about 96%, specificity about 100%, precision about 100%, and accuracy about 97% for globalization approach while, sensitivity about 100%, specificity about 100%, precision about 100%, and accuracy about 100% for Localization Approach, these results showed that the localization approach achieved acceptable accuracy and better than globalization approach for skin cancer lesions classification.

The effect of defect cluster size and interpolation on radiographic image quality

NASA Astrophysics Data System (ADS)

Töpfer, Karin; Yip, Kwok L.

2011-03-01

For digital X-ray detectors, the need to control factory yield and cost invariably leads to the presence of some defective pixels. Recently, a standard procedure was developed to identify such pixels for industrial applications. However, no quality standards exist in medical or industrial imaging regarding the maximum allowable number and size of detector defects. While the answer may be application specific, the minimum requirement for any defect specification is that the diagnostic quality of the images be maintained. A more stringent criterion is to keep any changes in the images due to defects below the visual threshold. Two highly sensitive image simulation and evaluation methods were employed to specify the fraction of allowable defects as a function of defect cluster size in general radiography. First, the most critical situation of the defect being located in the center of the disease feature was explored using image simulation tools and a previously verified human observer model, incorporating a channelized Hotelling observer. Detectability index d' was obtained as a function of defect cluster size for three different disease features on clinical lung and extremity backgrounds. Second, four concentrations of defects of four different sizes were added to clinical images with subtle disease features and then interpolated. Twenty observers evaluated the images against the original on a single display using a 2-AFC method, which was highly sensitive to small changes in image detail. Based on a 50% just-noticeable difference, the fraction of allowed defects was specified vs. cluster size.

Profiling pleural effusion cells by a diffraction imaging method

NASA Astrophysics Data System (ADS)

Al-Qaysi, Safaa; Hong, Heng; Wen, Yuhua; Lu, Jun Q.; Feng, Yuanming; Hu, Xin-Hua

2018-02-01

Assay of cells in pleural effusion (PE) is an important means of disease diagnosis. Conventional cytology of effusion samples, however, has low sensitivity and depends heavily on the expertise of cytopathologists. We applied a polarization diffraction imaging flow cytometry method on effusion cells to investigate their features. Diffraction imaging of the PE cell samples has been performed on 6000 to 12000 cells for each effusion cell sample of three patients. After prescreening to remove images by cellular debris and aggregated non-cellular particles, the image textures were extracted with a gray level co-occurrence matrix (GLCM) algorithm. The distribution of the imaged cells in the GLCM parameters space was analyzed by a Gaussian Mixture Model (GMM) to determine the number of clusters among the effusion cells. These results yield insight on textural features of diffraction images and related cellular morphology in effusion samples and can be used toward the development of a label-free method for effusion cells assay.

Quantitative imaging assay for NF-κB nuclear translocation in primary human macrophages

PubMed Central

Noursadeghi, Mahdad; Tsang, Jhen; Haustein, Thomas; Miller, Robert F.; Chain, Benjamin M.; Katz, David R.

2008-01-01

Quantitative measurement of NF-κB nuclear translocation is an important research tool in cellular immunology. Established methodologies have a number of limitations, such as poor sensitivity, high cost or dependence on cell lines. Novel imaging methods to measure nuclear translocation of transcriptionally active components of NF-κB are being used but are also partly limited by the need for specialist imaging equipment or image analysis software. Herein we present a method for quantitative detection of NF-κB rel A nuclear translocation, using immunofluorescence microscopy and the public domain image analysis software ImageJ that can be easily adopted for cellular immunology research without the need for specialist image analysis expertise and at low cost. The method presented here is validated by demonstrating the time course and dose response of NF-κB nuclear translocation in primary human macrophages stimulated with LPS, and by comparison with a commercial NF-κB activation reporter cell line. PMID:18036607

Imaging indicator for ESD safety testing.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Whinnery, LeRoy L.,; Nissen, April; Keifer, Patrick N.

2013-05-01

This report describes the development of a new detection method for electrostatic discharge (ESD) testing of explosives, using a single-lens reflex (SLR) digital camera and a 200-mm macro lens. This method has demonstrated several distinct advantages to other current ESD detection methods, including the creation of a permanent record, an enlarged image for real-time viewing as well as extended periods of review, and ability to combine with most other Go/No-Go sensors. This report includes details of the method, including camera settings and position, and results with wellcharacterized explosives PETN and RDX, and two ESD-sensitive aluminum powders.

Polarization sensitive spectroscopic optical coherence tomography for multimodal imaging

NASA Astrophysics Data System (ADS)

Strąkowski, Marcin R.; Kraszewski, Maciej; Strąkowska, Paulina; Trojanowski, Michał

2015-03-01

Optical coherence tomography (OCT) is a non-invasive method for 3D and cross-sectional imaging of biological and non-biological objects. The OCT measurements are provided in non-contact and absolutely safe way for the tested sample. Nowadays, the OCT is widely applied in medical diagnosis especially in ophthalmology, as well as dermatology, oncology and many more. Despite of great progress in OCT measurements there are still a vast number of issues like tissue recognition or imaging contrast enhancement that have not been solved yet. Here we are going to present the polarization sensitive spectroscopic OCT system (PS-SOCT). The PS-SOCT combines the polarization sensitive analysis with time-frequency analysis. Unlike standard polarization sensitive OCT the PS-SOCT delivers spectral information about measured quantities e.g. tested object birefringence changes over the light spectra. This solution overcomes the limits of polarization sensitive analysis applied in standard PS-OCT. Based on spectral data obtained from PS-SOCT the exact value of birefringence can be calculated even for the objects that provide higher order of retardation. In this contribution the benefits of using the combination of time-frequency and polarization sensitive analysis are being expressed. Moreover, the PS-SOCT system features, as well as OCT measurement examples are presented.

Direct Visualization of Short Transverse Relaxation Time Component (ViSTa)

PubMed Central

Oh, Se-Hong; Bilello, Michel; Schindler, Matthew; Markowitz, Clyde E.; Detre, John A.; Lee, Jongho

2013-01-01

White matter of the brain has been demonstrated to have multiple relaxation components. Among them, the short transverse relaxation time component (T2 < 40 ms; T2* < 25 ms at 3T) has been suggested to originate from myelin water whereas long transverse relaxation time components have been associated with axonal and/or interstitial water. In myelin water imaging, T2 or T2* signal decay is measured to estimate myelin water fraction based on T2 or T2* differences among the water components. This method has been demonstrated to be sensitive to demyelination in the brain but suffers from low SNR and image artifacts originating from ill-conditioned multi-exponential fitting. In this study, a novel approach that selectively acquires short transverse relaxation time signal is proposed. The method utilizes a double inversion RF pair to suppress a range of long T1 signal. This suppression leaves short T2* signal, which has been suggested to have short T1, as the primary source of the image. The experimental results confirms that after suppression of long T1 signals, the image is dominated by short T2* in the range of myelin water, allowing us to directly visualize the short transverse relaxation time component in the brain. Compared to conventional myelin water imaging, this new method of direct visualization of short relaxation time component (ViSTa) provides high quality images. When applied to multiple sclerosis patients, chronic lesions show significantly reduced signal intensity in ViSTa images suggesting sensitivity to demyelination. PMID:23796545

Application of nonlinear phenomena induced by focused ultrasound to bone imaging.

PubMed

Callé, Samuel; Remenieras, Jean-Pierre; Bou Matar, Olivier; Defontaine, Marielle; Patat, Frederic

2003-03-01

A tissue deformability image is obtained with the vibroacoustography imaging method using mechanical low-frequency (LF) excitation. This ultrasonic excitation is created locally by means of a focused annular array emitting two primary beams at two close frequencies, f(1) and f(2) (f(2) = f(1) + f(LF)). The LF acoustic emission resulting from the vibration of the medium is detected by a sensitive hydrophone and then used to form the image. This noninvasive imaging method was demonstrated in this study to be suitable for bone imaging, with x and y transverse resolutions less than 300 micro m. Two bone sites susceptible to demineralization were tested: the calcaneus and the neck of the femur. The vibroacoustic method provides valuable ultrasonic images regarding the structure and the elastic properties of bone tissue. Correlation was made between vibroacoustic bone images, performed in vitro, and images acquired by other imaging methods (i.e., bone ultrasound attenuation and x-ray computerized tomography (CT)). Moreover, the amplitudes of vibroacoustic signals radiating from phosphocalcic ceramic samples (bone substitute) of different porosity were evaluated. The good correlation between these results and the description of our images and the quality of vibroacoustic images indicate that bone decalcification could be detected using vibroacoustography.

SNR-optimized phase-sensitive dual-acquisition turbo spin echo imaging: a fast alternative to FLAIR.

PubMed

Lee, Hyunyeol; Park, Jaeseok

2013-07-01

Phase-sensitive dual-acquisition single-slab three-dimensional turbo spin echo imaging was recently introduced, producing high-resolution isotropic cerebrospinal fluid attenuated brain images without long inversion recovery preparation. Despite the advantages, the weighted-averaging-based technique suffers from noise amplification resulting from different levels of cerebrospinal fluid signal modulations over the two acquisitions. The purpose of this work is to develop a signal-to-noise ratio-optimized version of the phase-sensitive dual-acquisition single-slab three-dimensional turbo spin echo. Variable refocusing flip angles in the first acquisition are calculated using a three-step prescribed signal evolution while those in the second acquisition are calculated using a two-step pseudo-steady state signal transition with a high flip-angle pseudo-steady state at a later portion of the echo train, balancing the levels of cerebrospinal fluid signals in both the acquisitions. Low spatial frequency signals are sampled during the high flip-angle pseudo-steady state to further suppress noise. Numerical simulations of the Bloch equations were performed to evaluate signal evolutions of brain tissues along the echo train and optimize imaging parameters. In vivo studies demonstrate that compared with conventional phase-sensitive dual-acquisition single-slab three-dimensional turbo spin echo, the proposed optimization yields 74% increase in apparent signal-to-noise ratio for gray matter and 32% decrease in imaging time. The proposed method can be a potential alternative to conventional fluid-attenuated imaging. Copyright © 2012 Wiley Periodicals, Inc.

Class of near-perfect coded apertures

NASA Technical Reports Server (NTRS)

Cannon, T. M.; Fenimore, E. E.

1977-01-01

Coded aperture imaging of gamma ray sources has long promised an improvement in the sensitivity of various detector systems. The promise has remained largely unfulfilled, however, for either one of two reasons. First, the encoding/decoding method produces artifacts, which even in the absence of quantum noise, restrict the quality of the reconstructed image. This is true of most correlation-type methods. Second, if the decoding procedure is of the deconvolution variety, small terms in the transfer function of the aperture can lead to excessive noise in the reconstructed image. It is proposed to circumvent both of these problems by use of a uniformly redundant array (URA) as the coded aperture in conjunction with a special correlation decoding method.

A novel speckle pattern—Adaptive digital image correlation approach with robust strain calculation

NASA Astrophysics Data System (ADS)

Cofaru, Corneliu; Philips, Wilfried; Van Paepegem, Wim

2012-02-01

Digital image correlation (DIC) has seen widespread acceptance and usage as a non-contact method for the determination of full-field displacements and strains in experimental mechanics. The advances of imaging hardware in the last decades led to high resolution and speed cameras being more affordable than in the past making large amounts of data image available for typical DIC experimental scenarios. The work presented in this paper is aimed at maximizing both the accuracy and speed of DIC methods when employed with such images. A low-level framework for speckle image partitioning which replaces regularly shaped blocks with image-adaptive cells in the displacement calculation is introduced. The Newton-Raphson DIC method is modified to use the image pixels of the cells and to perform adaptive regularization to increase the spatial consistency of the displacements. Furthermore, a novel robust framework for strain calculation based also on the Newton-Raphson algorithm is introduced. The proposed methods are evaluated in five experimental scenarios, out of which four use numerically deformed images and one uses real experimental data. Results indicate that, as the desired strain density increases, significant computational gains can be obtained while maintaining or improving accuracy and rigid-body rotation sensitivity.

Description-based reappraisal regulate the emotion induced by erotic and neutral images in a Chinese population.

PubMed

Peng, Jiaxin; Qu, Chen; Gu, Ruolei; Luo, Yue-Jia

2012-01-01

Previous emotion-regulation research has shown that the late positive potential (LPP) is sensitive to the down-regulation of emotion; however, whether LPP is also sensitive to the up-regulation of emotion remains unclear. The present study examined the description-based reappraisal effects on the up-regulation of positive emotions induced by erotic and neutral images in a Chinese population. Self-reported ratings and event-related potential (ERP) were recorded when subjects viewed pleasant and neutral images, which were shown after either a neutral or positive description. Self-reported results showed that images following positive descriptions were rated as more pleasant compared to images following neutral descriptions. ERP results revealed that the P2, P3, and slow wave (SW) components were larger for erotic pictures than for neutral pictures, while the positive description condition yielded attenuated erotic image-induced P2, P3 and SW and increased SW induced by neutral images. The results demonstrated that description-based reappraisal, as a method of reappraisal, significantly modulates the emotional experience and ERP responses to erotic and neutral images.

Wavelet analysis enables system-independent texture analysis of optical coherence tomography images.

PubMed

Lingley-Papadopoulos, Colleen A; Loew, Murray H; Zara, Jason M

2009-01-01

Texture analysis for tissue characterization is a current area of optical coherence tomography (OCT) research. We discuss some of the differences between OCT systems and the effects those differences have on the resulting images and subsequent image analysis. In addition, as an example, two algorithms for the automatic recognition of bladder cancer are compared: one that was developed on a single system with no consideration for system differences, and one that was developed to address the issues associated with system differences. The first algorithm had a sensitivity of 73% and specificity of 69% when tested using leave-one-out cross-validation on data taken from a single system. When tested on images from another system with a different central wavelength, however, the method classified all images as cancerous regardless of the true pathology. By contrast, with the use of wavelet analysis and the removal of system-dependent features, the second algorithm reported sensitivity and specificity values of 87 and 58%, respectively, when trained on images taken with one imaging system and tested on images taken with another.

Description-based reappraisal regulate the emotion induced by erotic and neutral images in a Chinese population

PubMed Central

Peng, Jiaxin; Qu, Chen; Gu, Ruolei; Luo, Yue-Jia

2013-01-01

Previous emotion-regulation research has shown that the late positive potential (LPP) is sensitive to the down-regulation of emotion; however, whether LPP is also sensitive to the up-regulation of emotion remains unclear. The present study examined the description-based reappraisal effects on the up-regulation of positive emotions induced by erotic and neutral images in a Chinese population. Self-reported ratings and event-related potential (ERP) were recorded when subjects viewed pleasant and neutral images, which were shown after either a neutral or positive description. Self-reported results showed that images following positive descriptions were rated as more pleasant compared to images following neutral descriptions. ERP results revealed that the P2, P3, and slow wave (SW) components were larger for erotic pictures than for neutral pictures, while the positive description condition yielded attenuated erotic image-induced P2, P3 and SW and increased SW induced by neutral images. The results demonstrated that description-based reappraisal, as a method of reappraisal, significantly modulates the emotional experience and ERP responses to erotic and neutral images. PMID:23335894

Wavelet analysis enables system-independent texture analysis of optical coherence tomography images

NASA Astrophysics Data System (ADS)

Lingley-Papadopoulos, Colleen A.; Loew, Murray H.; Zara, Jason M.

2009-07-01

Texture analysis for tissue characterization is a current area of optical coherence tomography (OCT) research. We discuss some of the differences between OCT systems and the effects those differences have on the resulting images and subsequent image analysis. In addition, as an example, two algorithms for the automatic recognition of bladder cancer are compared: one that was developed on a single system with no consideration for system differences, and one that was developed to address the issues associated with system differences. The first algorithm had a sensitivity of 73% and specificity of 69% when tested using leave-one-out cross-validation on data taken from a single system. When tested on images from another system with a different central wavelength, however, the method classified all images as cancerous regardless of the true pathology. By contrast, with the use of wavelet analysis and the removal of system-dependent features, the second algorithm reported sensitivity and specificity values of 87 and 58%, respectively, when trained on images taken with one imaging system and tested on images taken with another.

An improved three-dimensional non-scanning laser imaging system based on digital micromirror device

NASA Astrophysics Data System (ADS)

Xia, Wenze; Han, Shaokun; Lei, Jieyu; Zhai, Yu; Timofeev, Alexander N.

2018-01-01

Nowadays, there are two main methods to realize three-dimensional non-scanning laser imaging detection, which are detection method based on APD and detection method based on Streak Tube. However, the detection method based on APD possesses some disadvantages, such as small number of pixels, big pixel interval and complex supporting circuit. The detection method based on Streak Tube possesses some disadvantages, such as big volume, bad reliability and high cost. In order to resolve the above questions, this paper proposes an improved three-dimensional non-scanning laser imaging system based on Digital Micromirror Device. In this imaging system, accurate control of laser beams and compact design of imaging structure are realized by several quarter-wave plates and a polarizing beam splitter. The remapping fiber optics is used to sample the image plane of receiving optical lens, and transform the image into line light resource, which can realize the non-scanning imaging principle. The Digital Micromirror Device is used to convert laser pulses from temporal domain to spatial domain. The CCD with strong sensitivity is used to detect the final reflected laser pulses. In this paper, we also use an algorithm which is used to simulate this improved laser imaging system. In the last, the simulated imaging experiment demonstrates that this improved laser imaging system can realize three-dimensional non-scanning laser imaging detection.

Normalized Temperature Contrast Processing in Flash Infrared Thermography

NASA Technical Reports Server (NTRS)

Koshti, Ajay M.

2016-01-01

The paper presents further development in normalized contrast processing of flash infrared thermography method by the author given in US 8,577,120 B1. The method of computing normalized image or pixel intensity contrast, and normalized temperature contrast are provided, including converting one from the other. Methods of assessing emissivity of the object, afterglow heat flux, reflection temperature change and temperature video imaging during flash thermography are provided. Temperature imaging and normalized temperature contrast imaging provide certain advantages over pixel intensity normalized contrast processing by reducing effect of reflected energy in images and measurements, providing better quantitative data. The subject matter for this paper mostly comes from US 9,066,028 B1 by the author. Examples of normalized image processing video images and normalized temperature processing video images are provided. Examples of surface temperature video images, surface temperature rise video images and simple contrast video images area also provided. Temperature video imaging in flash infrared thermography allows better comparison with flash thermography simulation using commercial software which provides temperature video as the output. Temperature imaging also allows easy comparison of surface temperature change to camera temperature sensitivity or noise equivalent temperature difference (NETD) to assess probability of detecting (POD) anomalies.

A fast method for detecting Cryptosporidium parvum oocysts in real world samples

NASA Astrophysics Data System (ADS)

Stewart, Shona; McClelland, Lindy; Maier, John

2005-04-01

Contamination of drinking water with pathogenic microorganisms such as Cryptosporidium has become an increasing concern in recent years. Cryptosporidium oocysts are particularly problematic, as infections caused by this organism can be life threatening in immunocompromised patients. Current methods for monitoring and analyzing water are often laborious and require experts to conduct. In addition, many of the techniques require very specific reagents to be employed. These factors add considerable cost and time to the analytical process. Raman spectroscopy provides specific molecular information on samples, and offers advantages of speed, sensitivity and low cost over current methods of water monitoring. Raman spectroscopy is an optical method that has demonstrated the capability to identify and differentiate microorganisms at the species and strain levels. In addition, this technique has exhibited sensitivities down to the single organism detection limit. We have employed Raman spectroscopy and Raman Chemical Imaging, in conjunction with chemometric techniques, to detect small numbers of oocysts in the presence of interferents derived from real-world water samples. Our investigations have also indicated that Raman Chemical Imaging may provide chemical and physiological information about an oocyst sample which complements information provided by the traditional methods. This work provides evidence that Raman imaging is a useful technique for consideration in the water quality industry.

Tip/tilt-compensated through-focus scanning optical microscopy

NASA Astrophysics Data System (ADS)

Lee, Jun Ho; Park, Jun Hyung; Jeong, Dohwan; Shin, Eun Ji; Park, Chris

2016-11-01

Through-Focus Optical Microscopy (TSOM), with nanometer scale lateral and vertical sensitivity matching those of scanning electron microscopy, has been demonstrated to be utilized for 3D inspection and metrology. There have been sensitivity and instability issues in acquiring through-focus images because TSOM 3D information is indirectly extracted by differentiating a target TSOM image from reference TSOM images. This paper first reports on the optical axis instability that occurs during the scanning process of TSOM when implemented in an existing patterned wafer inspection tool by moving the wafer plane; this is followed by quantitative confirmation of the optical/mechanical instability using a new TSOM tool on an optical bench with a Shack-Hartmann wavefront sensor and a tip/tilt sensor. Then, this paper proposes two tip/tilt compensated TSOM optical acquisition methods that can be applied with adaptive optics. The first method simply adopts a tip/tilt mirror with a quad cell in a simple closed loop, while the second method adopts a highorder deformable mirror with a Shack-Hartmann sensor. The second method is able to correct high-order residual aberrations as well as to perform through-focus scanning without z-axis movement, while the first method is easier to implement in pre-existing wafer inspection systems with only minor modification.

Comparison of Short-Wavelength Reduced-Illuminance and Conventional Autofluorescence Imaging in Stargardt Macular Dystrophy.

PubMed

Strauss, Rupert W; Muñoz, Beatriz; Jha, Anamika; Ho, Alexander; Cideciyan, Artur V; Kasilian, Melissa L; Wolfson, Yulia; Sadda, SriniVas; West, Sheila; Scholl, Hendrik P N; Michaelides, Michel

2016-08-01

To compare grading results between short-wavelength reduced-illuminance and conventional autofluorescence imaging in Stargardt macular dystrophy. Reliability study. setting: Moorfields Eye Hospital, London (United Kingdom). Eighteen patients (18 eyes) with Stargardt macular dystrophy. A series of 3 fundus autofluorescence images using 3 different acquisition parameters on a custom-patched device were obtained: (1) 25% laser power and total sensitivity 87; (2) 25% laser power and freely adjusted sensitivity; and (3) 100% laser power and freely adjusted total sensitivity (conventional). The total area of 2 hypoautofluorescent lesion types (definitely decreased autofluorescence and poorly demarcated questionably decreased autofluorescence) was measured. Agreement in grading between the 3 imaging methods was assessed by kappa coefficients (κ) and intraclass correlation coefficients. The mean ± standard deviation area for images acquired with 25% laser power and freely adjusted total sensitivity was 2.04 ± 1.87 mm(2) for definitely decreased autofluorescence (n = 15) and 1.86 ± 2.14 mm(2) for poorly demarcated questionably decreased autofluorescence (n = 12). The intraclass correlation coefficient (95% confidence interval) was 0.964 (0.929, 0.999) for definitely decreased autofluorescence and 0.268 (0.000, 0.730) for poorly demarcated questionably decreased autofluorescence. Short-wavelength reduced-illuminance and conventional fundus autofluorescence imaging showed good concordance in assessing areas of definitely decreased autofluorescence. However, there was significantly higher variability between imaging modalities for assessing areas of poorly demarcated questionably decreased autofluorescence. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Brachial artery vasomotion and transducer pressure effect on measurements by active contour segmentation on ultrasound

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cary, Theodore W.; Sultan, Laith R.; Sehgal, Chandra M., E-mail: sehgalc@uphs.upenn.edu

Purpose: To use feed-forward active contours (snakes) to track and measure brachial artery vasomotion on ultrasound images recorded in both transverse and longitudinal views; and to compare the algorithm's performance in each view. Methods: Longitudinal and transverse view ultrasound image sequences of 45 brachial arteries were segmented by feed-forward active contour (FFAC). The segmented regions were used to measure vasomotion artery diameter, cross-sectional area, and distention both as peak-to-peak diameter and as area. ECG waveforms were also simultaneously extracted frame-by-frame by thresholding a running finite-difference image between consecutive images. The arterial and ECG waveforms were compared as they traced eachmore » phase of the cardiac cycle. Results: FFAC successfully segmented arteries in longitudinal and transverse views in all 45 cases. The automated analysis took significantly less time than manual tracing, but produced superior, well-behaved arterial waveforms. Automated arterial measurements also had lower interobserver variability as measured by correlation, difference in mean values, and coefficient of variation. Although FFAC successfully segmented both the longitudinal and transverse images, transverse measurements were less variable. The cross-sectional area computed from the longitudinal images was 27% lower than the area measured from transverse images, possibly due to the compression of the artery along the image depth by transducer pressure. Conclusions: FFAC is a robust and sensitive vasomotion segmentation algorithm in both transverse and longitudinal views. Transverse imaging may offer advantages over longitudinal imaging: transverse measurements are more consistent, possibly because the method is less sensitive to variations in transducer pressure during imaging.« less

Brachial artery vasomotion and transducer pressure effect on measurements by active contour segmentation on ultrasound

PubMed Central

Cary, Theodore W.; Reamer, Courtney B.; Sultan, Laith R.; Mohler, Emile R.; Sehgal, Chandra M.

2014-01-01

Purpose: To use feed-forward active contours (snakes) to track and measure brachial artery vasomotion on ultrasound images recorded in both transverse and longitudinal views; and to compare the algorithm's performance in each view. Methods: Longitudinal and transverse view ultrasound image sequences of 45 brachial arteries were segmented by feed-forward active contour (FFAC). The segmented regions were used to measure vasomotion artery diameter, cross-sectional area, and distention both as peak-to-peak diameter and as area. ECG waveforms were also simultaneously extracted frame-by-frame by thresholding a running finite-difference image between consecutive images. The arterial and ECG waveforms were compared as they traced each phase of the cardiac cycle. Results: FFAC successfully segmented arteries in longitudinal and transverse views in all 45 cases. The automated analysis took significantly less time than manual tracing, but produced superior, well-behaved arterial waveforms. Automated arterial measurements also had lower interobserver variability as measured by correlation, difference in mean values, and coefficient of variation. Although FFAC successfully segmented both the longitudinal and transverse images, transverse measurements were less variable. The cross-sectional area computed from the longitudinal images was 27% lower than the area measured from transverse images, possibly due to the compression of the artery along the image depth by transducer pressure. Conclusions: FFAC is a robust and sensitive vasomotion segmentation algorithm in both transverse and longitudinal views. Transverse imaging may offer advantages over longitudinal imaging: transverse measurements are more consistent, possibly because the method is less sensitive to variations in transducer pressure during imaging. PMID:24506648

Development of gamma-photon/Cerenkov-light hybrid system for simultaneous imaging of I-131 radionuclide

NASA Astrophysics Data System (ADS)

Yamamoto, Seiichi; Suzuki, Mayumi; Kato, Katsuhiko; Watabe, Tadashi; Ikeda, Hayato; Kanai, Yasukazu; Ogata, Yoshimune; Hatazawa, Jun

2016-09-01

Although iodine 131 (I-131) is used for radionuclide therapy, high resolution images are difficult to obtain with conventional gamma cameras because of the high energy of I-131 gamma photons (364 keV). Cerenkov-light imaging is a possible method for beta emitting radionuclides, and I-131 (606 MeV maximum beta energy) is a candidate to obtain high resolution images. We developed a high energy gamma camera system for I-131 radionuclide and combined it with a Cerenkov-light imaging system to form a gamma-photon/Cerenkov-light hybrid imaging system to compare the simultaneously measured images of these two modalities. The high energy gamma imaging detector used 0.85-mm×0.85-mm×10-mm thick GAGG scintillator pixels arranged in a 44×44 matrix with a 0.1-mm thick reflector and optical coupled to a Hamamatsu 2 in. square position sensitive photomultiplier tube (PSPMT: H12700 MOD). The gamma imaging detector was encased in a 2 cm thick tungsten shield, and a pinhole collimator was mounted on its top to form a gamma camera system. The Cerenkov-light imaging system was made of a high sensitivity cooled CCD camera. The Cerenkov-light imaging system was combined with the gamma camera using optical mirrors to image the same area of the subject. With this configuration, we simultaneously imaged the gamma photons and the Cerenkov-light from I-131 in the subjects. The spatial resolution and sensitivity of the gamma camera system for I-131 were respectively 3 mm FWHM and 10 cps/MBq for the high sensitivity collimator at 10 cm from the collimator surface. The spatial resolution of the Cerenkov-light imaging system was 0.64 mm FWHM at 10 cm from the system surface. Thyroid phantom and rat images were successfully obtained with the developed gamma-photon/Cerenkov-light hybrid imaging system, allowing direct comparison of these two modalities. Our developed gamma-photon/Cerenkov-light hybrid imaging system will be useful to evaluate the advantages and disadvantages of these two modalities.

High Sensitivity Detection of Broadband Acoustic Vibration Using Optical Demodulation Method

NASA Astrophysics Data System (ADS)

Zhang, Zhen

Measuring the high frequency acoustic vibrations represents the fundamental interest in revealing the intrinsic dynamic characteristic of board range of systems, such as the growth of the fetus, blood flow in human palms, and vibrations of carbon nanotube. However, the acoustic wave detection capability is limited by the detection bandwidth and sensitivity of the commonly used piezoelectric based ultrasound detectors. To overcome these limitations, this thesis focuses on exploring the optical demodulation method for highly sensitive detection of broadband acoustic vibration. First, a transparent optical ultrasonic detector has been developed using micro-ring resonator (MRR) made of soft polymeric materials. It outperforms the traditional piezoelectric detectors with broader detection bandwidth, miniaturized size and wide angular sensitivity. Its ease of integration into photoacoustic microscopy system has resulted in the great improvement of the imaging resolution. A theoretic framework has been developed to establish the quantitative understanding of its unique distance and angular dependent detection characteristics and was subsequently validated experimentally. The developed theoretic framework provides a guideline to fully accounts for the trade-offs between axial and lateral resolution, working distance, and the field of view in developing optimal imaging performance for a wide range of biological and clinical applications. MRR-based ultrasonic detector is further integrated into confocal fluorescence microscopy to realize the simultaneous imaging of fluorescence and optical absorption of retinal pigment epithelium, achieving multi-contrast imaging at sub-cellular level. The needs to resolve the fine details of the biological specimen with the resolution beyond the diffraction limit further motivate the development of optical demodulated ultrasonic detection method based on near-field scanning optical microscopy (NSOM). The nano-focusing probe was developed for adiabatic focusing of surface plasmon polaritons to the probe apex with high energy efficiency and the suppression of the background noise was accomplished through the implementation of the harmonic demodulation technique. Collectively, this system is capable of delivering intense near-field illumination source while effectively suppressing the background signal due to the far-field scattering and thus, allows for quantitative mapping of local evanescent field with enhanced contrast and improved resolutions. The performance of the developed NSOM system has been validated through the experimental measurements of the surface plasmon polariton mode. This new NSOM system enables optical demodulated ultrasound detection at nanoscale spatial resolution. Using it to detect the ultrasound signal within the acoustic near-field has led to the successful experimental demonstration of the sub-surface photoacoustic imaging of buried objects with sub-diffraction-limited resolution and high sensitivity. Such a new ultrasound detection method holds promising potential for super-resolution ultrasound imaging.

Review of SPECT collimator selection, optimization, and fabrication for clinical and preclinical imaging

PubMed Central

Van Audenhaege, Karen; Van Holen, Roel; Vandenberghe, Stefaan; Vanhove, Christian; Metzler, Scott D.; Moore, Stephen C.

2015-01-01

In single photon emission computed tomography, the choice of the collimator has a major impact on the sensitivity and resolution of the system. Traditional parallel-hole and fan-beam collimators used in clinical practice, for example, have a relatively poor sensitivity and subcentimeter spatial resolution, while in small-animal imaging, pinhole collimators are used to obtain submillimeter resolution and multiple pinholes are often combined to increase sensitivity. This paper reviews methods for production, sensitivity maximization, and task-based optimization of collimation for both clinical and preclinical imaging applications. New opportunities for improved collimation are now arising primarily because of (i) new collimator-production techniques and (ii) detectors with improved intrinsic spatial resolution that have recently become available. These new technologies are expected to impact the design of collimators in the future. The authors also discuss concepts like septal penetration, high-resolution applications, multiplexing, sampling completeness, and adaptive systems, and the authors conclude with an example of an optimization study for a parallel-hole, fan-beam, cone-beam, and multiple-pinhole collimator for different applications. PMID:26233207

Brain tumor segmentation using holistically nested neural networks in MRI images.

PubMed

Zhuge, Ying; Krauze, Andra V; Ning, Holly; Cheng, Jason Y; Arora, Barbara C; Camphausen, Kevin; Miller, Robert W

2017-10-01

Gliomas are rapidly progressive, neurologically devastating, largely fatal brain tumors. Magnetic resonance imaging (MRI) is a widely used technique employed in the diagnosis and management of gliomas in clinical practice. MRI is also the standard imaging modality used to delineate the brain tumor target as part of treatment planning for the administration of radiation therapy. Despite more than 20 yr of research and development, computational brain tumor segmentation in MRI images remains a challenging task. We are presenting a novel method of automatic image segmentation based on holistically nested neural networks that could be employed for brain tumor segmentation of MRI images. Two preprocessing techniques were applied to MRI images. The N4ITK method was employed for correction of bias field distortion. A novel landmark-based intensity normalization method was developed so that tissue types have a similar intensity scale in images of different subjects for the same MRI protocol. The holistically nested neural networks (HNN), which extend from the convolutional neural networks (CNN) with a deep supervision through an additional weighted-fusion output layer, was trained to learn the multiscale and multilevel hierarchical appearance representation of the brain tumor in MRI images and was subsequently applied to produce a prediction map of the brain tumor on test images. Finally, the brain tumor was obtained through an optimum thresholding on the prediction map. The proposed method was evaluated on both the Multimodal Brain Tumor Image Segmentation (BRATS) Benchmark 2013 training datasets, and clinical data from our institute. A dice similarity coefficient (DSC) and sensitivity of 0.78 and 0.81 were achieved on 20 BRATS 2013 training datasets with high-grade gliomas (HGG), based on a two-fold cross-validation. The HNN model built on the BRATS 2013 training data was applied to ten clinical datasets with HGG from a locally developed database. DSC and sensitivity of 0.83 and 0.85 were achieved. A quantitative comparison indicated that the proposed method outperforms the popular fully convolutional network (FCN) method. In terms of efficiency, the proposed method took around 10 h for training with 50,000 iterations, and approximately 30 s for testing of a typical MRI image in the BRATS 2013 dataset with a size of 160 × 216 × 176, using a DELL PRECISION workstation T7400, with an NVIDIA Tesla K20c GPU. An effective brain tumor segmentation method for MRI images based on a HNN has been developed. The high level of accuracy and efficiency make this method practical in brain tumor segmentation. It may play a crucial role in both brain tumor diagnostic analysis and in the treatment planning of radiation therapy. Published 2017. This article is a U.S. Government work and is in the public domain in the USA.

Near Infrared Imaging as a Diagnostic Tool for Detecting Enamel Demineralization: An in vivo Study

NASA Astrophysics Data System (ADS)

Lucas, Seth Adam

Background and Objectives: For decades there has been an effort to develop alternative optical methods of imaging dental decay utilizing non-ionizing radiation methods. The purpose of this in-vivo study was to demonstrate whether NIR can be used as a diagnostic tool to evaluate dental caries and to compare the sensitivity and specificity of this method with that of conventional methods, including bitewing x-rays and visual inspection. Materials and Methods: 31 test subjects (n=31) from the UCSF orthodontic clinic undergoing orthodontic treatment with planned premolar extractions were recruited. Calibrated examiners performed caries detection examinations using conventional methods: bitewing radiographs and visual inspection. These findings were compared with the results from NIR examinations: transillumination and reflectance. To confirm the results found in the two different detection methods, a gold standard was used. After teeth were extracted, polarized light microscopy and transverse microradiography were performed. Results: A total of 87 premolars were used in the study. NIR identified the occlusal lesions with a sensitivity of 71% and a specificity of 77%, whereas, the visual examination had a sensitivity of only 40% and a specifity of 39%. For interproximal lesions halfway to DEJ, specificity remained constant, but sensitivity improved to 100% for NIR and 75% for x-rays. Conclusions: The results of this preliminary study demonstrate that NIR is just as effective at detecting enamel interproximal lesions as standard dental x-rays. NIR was more effective at detecting occlusal lesions than visual examination alone. NIR shows promise as an alternative diagnostic tool to the conventional methods of x-rays and visual examination and provides a non-ionizing radiation technique.

Uncertainty quantification of fiber orientation distribution measurements for long-fiber-reinforced thermoplastic composites

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sharma, Bhisham N.; Naragani, Diwakar; Nguyen, Ba Nghiep

We present a detailed methodology for experimental measurement of fiber orientation distribution (FOD) in injection-molded discontinuous fiber composites using the method of ellipses on 2D cross sections. Best practices to avoid biases occurring during surface preparation and optical imaging of carbon-fiber-reinforced thermoplastics are discussed. A marker-based watershed transform routine for efficient image segmentation and the separation of touching fiber ellipses is developed. The sensitivity of the averaged orientation tensor to the image sample size is studied for the case of long-fiber thermoplastics. A Mori-Tanaka implementation of the Eshelby model is then employed to quantify the sensitivity of elastic stiffness predictionsmore » to biases in the FOD measurements.« less

Uncertainty quantification of fiber orientation distribution measurements for long-fiber-reinforced thermoplastic composites

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sharma, Bhisham N.; Naragani, Diwakar; Nguyen, Ba Nghiep

Here, we present a detailed methodology for experimental measurement of fiber orientation distribution in injection-molded discontinuous fiber composites using the method of ellipses on two-dimensional cross sections. Best practices to avoid biases occurring during surface preparation and optical imaging of carbon-fiber-reinforced thermoplastics are discussed. We developed a marker-based watershed transform routine for efficient image segmentation and the separation of touching fiber ellipses. The sensitivity of the averaged orientation tensor to the image sample size is studied for the case of long-fiber thermoplastics. A Mori–Tanaka implementation of the Eshelby model is then employed to quantify the sensitivity of elastic stiffness predictionsmore » to biases in the fiber orientation distribution measurements.« less

Uncertainty quantification of fiber orientation distribution measurements for long-fiber-reinforced thermoplastic composites

DOE PAGES

Sharma, Bhisham N.; Naragani, Diwakar; Nguyen, Ba Nghiep; ...

2017-09-28

Here, we present a detailed methodology for experimental measurement of fiber orientation distribution in injection-molded discontinuous fiber composites using the method of ellipses on two-dimensional cross sections. Best practices to avoid biases occurring during surface preparation and optical imaging of carbon-fiber-reinforced thermoplastics are discussed. We developed a marker-based watershed transform routine for efficient image segmentation and the separation of touching fiber ellipses. The sensitivity of the averaged orientation tensor to the image sample size is studied for the case of long-fiber thermoplastics. A Mori–Tanaka implementation of the Eshelby model is then employed to quantify the sensitivity of elastic stiffness predictionsmore » to biases in the fiber orientation distribution measurements.« less

A sub-sampled approach to extremely low-dose STEM

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stevens, A.; Luzi, L.; Yang, H.

The inpainting of randomly sub-sampled images acquired by scanning transmission electron microscopy (STEM) is an attractive method for imaging under low-dose conditions (≤ 1 e -Å 2) without changing either the operation of the microscope or the physics of the imaging process. We show that 1) adaptive sub-sampling increases acquisition speed, resolution, and sensitivity; and 2) random (non-adaptive) sub-sampling is equivalent, but faster than, traditional low-dose techniques. Adaptive sub-sampling opens numerous possibilities for the analysis of beam sensitive materials and in-situ dynamic processes at the resolution limit of the aberration corrected microscope and is demonstrated here for the analysis ofmore » the node distribution in metal-organic frameworks (MOFs).« less

The role of modern diagnostic imaging in diagnosing and differentiating kidney diseases in children.

PubMed

Maliborski, Artur; Zegadło, Arkadiusz; Placzyńska, Małgorzata; Sopińska, Małgorzata; Lichosik, Marianna; Jobs, Katarzyna

2018-01-01

Urinary tract diseases are in the group of the most commonly diagnosed medical conditions in pediatric patients. Many diseases with different etiologies are accompanied by pain, fever, hematuria, or urinary tract dysfunction. Those most common ones in children are urinary tract infections and congenital malformation. They can also represent tumors or changes caused by systemic diseases. Clinical tests and even more often additional imaging studies are required to make a proper diagnosis of urinary tract diseases. Just a few decades ago urography, cystography or voiding cystourethrography were the main methods in diagnostic imaging of the urinary tract. Today's imaging methods supported by digital radiographic and fluoroscopy systems, high sensitivity detectors with quantum detection, advanced algorithms eliminating motion artifacts, modern medical imaging monitors with a resolution of three or even eight megapixels significantly differ from conventional radiographic methods. The methods that are currently usually performed are: computed tomography, magnetic resonance imaging, isotopic methods and ultrasonography using elastography and new solutions in Doppler imaging. Modern techniques are currently focused on reducing radiation exposure with better imaging capabilities. The development of these techniques became an essential diagnostic aid in nephrological and urological practice. The aim of this paper is to present the latest solutions that are currently used in the diagnostic imaging of urinary tract diseases.

High compression image and image sequence coding

NASA Technical Reports Server (NTRS)

Kunt, Murat

1989-01-01

The digital representation of an image requires a very large number of bits. This number is even larger for an image sequence. The goal of image coding is to reduce this number, as much as possible, and reconstruct a faithful duplicate of the original picture or image sequence. Early efforts in image coding, solely guided by information theory, led to a plethora of methods. The compression ratio reached a plateau around 10:1 a couple of years ago. Recent progress in the study of the brain mechanism of vision and scene analysis has opened new vistas in picture coding. Directional sensitivity of the neurones in the visual pathway combined with the separate processing of contours and textures has led to a new class of coding methods capable of achieving compression ratios as high as 100:1 for images and around 300:1 for image sequences. Recent progress on some of the main avenues of object-based methods is presented. These second generation techniques make use of contour-texture modeling, new results in neurophysiology and psychophysics and scene analysis.

Recovery and normalization of triple coincidences in PET

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lage, Eduardo, E-mail: elage@mit.edu; Parot, Vicente; Dave, Shivang R.

2015-03-15

Purpose: Triple coincidences in positron emission tomography (PET) are events in which three γ-rays are detected simultaneously. These events, though potentially useful for enhancing the sensitivity of PET scanners, are discarded or processed without special consideration in current systems, because there is not a clear criterion for assigning them to a unique line-of-response (LOR). Methods proposed for recovering such events usually rely on the use of highly specialized detection systems, hampering general adoption, and/or are based on Compton-scatter kinematics and, consequently, are limited in accuracy by the energy resolution of standard PET detectors. In this work, the authors propose amore » simple and general solution for recovering triple coincidences, which does not require specialized detectors or additional energy resolution requirements. Methods: To recover triple coincidences, the authors’ method distributes such events among their possible LORs using the relative proportions of double coincidences in these LORs. The authors show analytically that this assignment scheme represents the maximum-likelihood solution for the triple-coincidence distribution problem. The PET component of a preclinical PET/CT scanner was adapted to enable the acquisition and processing of triple coincidences. Since the efficiencies for detecting double and triple events were found to be different throughout the scanner field-of-view, a normalization procedure specific for triple coincidences was also developed. The effect of including triple coincidences using their method was compared against the cases of equally weighting the triples among their possible LORs and discarding all the triple events. The authors used as figures of merit for this comparison sensitivity, noise-equivalent count (NEC) rates and image quality calculated as described in the NEMA NU-4 protocol for the assessment of preclinical PET scanners. Results: The addition of triple-coincidence events with the authors’ method increased peak NEC rates of the scanner by 26.6% and 32% for mouse- and rat-sized objects, respectively. This increase in NEC-rate performance was also reflected in the image-quality metrics. Images reconstructed using double and triple coincidences recovered using their method had better signal-to-noise ratio than those obtained using only double coincidences, while preserving spatial resolution and contrast. Distribution of triple coincidences using an equal-weighting scheme increased apparent system sensitivity but degraded image quality. The performance boost provided by the inclusion of triple coincidences using their method allowed to reduce the acquisition time of standard imaging procedures by up to ∼25%. Conclusions: Recovering triple coincidences with the proposed method can effectively increase the sensitivity of current clinical and preclinical PET systems without compromising other parameters like spatial resolution or contrast.« less

A simple method for MR elastography: a gradient-echo type multi-echo sequence.

PubMed

Numano, Tomokazu; Mizuhara, Kazuyuki; Hata, Junichi; Washio, Toshikatsu; Homma, Kazuhiro

2015-01-01

To demonstrate the feasibility of a novel MR elastography (MRE) technique based on a conventional gradient-echo type multi-echo MR sequence which does not need additional bipolar magnetic field gradients (motion encoding gradient: MEG), yet is sensitive to vibration. In a gradient-echo type multi-echo MR sequence, several images are produced from each echo of the train with different echo times (TEs). If these echoes are synchronized with the vibration, each readout's gradient lobes achieve a MEG-like effect, and the later generated echo causes a greater MEG-like effect. The sequence was tested for the tissue-mimicking agarose gel phantoms and the psoas major muscles of healthy volunteers. It was confirmed that the readout gradient lobes caused an MEG-like effect and the later TE images had higher sensitivity to vibrations. The magnitude image of later generated echo suffered the T2 decay and the susceptibility artifacts, but the wave image and elastogram of later generated echo were unaffected by these effects. In in vivo experiments, this method was able to measure the mean shear modulus of the psoas major muscle. From the results of phantom experiments and volunteer studies, it was shown that this method has clinical application potential. Copyright © 2014 Elsevier Inc. All rights reserved.

SENSITIVITY OF ENDOSCOPIC ULTRASOUND, MULTIDETECTOR COMPUTER TOMOGRAPHY AND MAGNETIC RESONANCE CHOLANGIOPANCREATOGRAPHY IN THE DIAGNOSIS OF PANCREAS DIVISUM: A TERTIARY CENTER EXPERIENCE

PubMed Central

Kushnir, Vladimir M.; Wani, Sachin B.; Fowler, Kathryn; Menias, Christine; Varma, Rakesh; Narra, Vamsi; Hovis, Christine; Murad, Faris; Mullady, Daniel; Jonnalagadda, Sreenivasa S.; Early, Dayna S.; Edmundowicz, Steven A.; Azar, Riad R.

2014-01-01

OBJECTIVES There are limited data comparing imaging modalities in the diagnosis of pancreas divisum. We aimed to: 1. Evaluate the sensitivity of endoscopic ultrasound (EUS), magnetic resonance cholangiopancreatography (MRCP) and multi-detector computed tomography (MDCT) for pancreas divisum. 2. Assess interobserver agreement (IOA) among expert radiologists for detecting pancreas divisum on MDCT and MRCP. METHODS For this retrospective cohort study, we identified 45 consecutive patients with pancreaticobiliary symptoms and pancreas divisum established by endoscopic retrograde pancreatography (ERP) who underwent EUS and cross-sectional imaging. The control group was composed of patients without pancreas divisum who underwent ERP and cross-sectional imaging. RESULTS The sensitivity of EUS for pancreas divisum was 86.7%, significantly higher than sensitivity reported in the medical records for MDCT (15.5%) or MRCP (60%) [p<0.001 for each]. On review by expert radiologists the sensitivity of MDCT increased to 83.3% in cases where the pancreatic duct was visualized, with fair IOA (қ=0.34). Expert review of MRCPs did not identify any additional cases of pancreas divisum; IOA was moderate (қ=0.43). CONCLUSIONS EUS is a sensitive test for diagnosing pancreas divisum and is superior to MDCT and MRCP. Review of MDCT studies by expert radiologists substantially raises its sensitivity for pancreas divisum. PMID:23211370

Predicting the need for CT imaging in children with minor head injury using an ensemble of Naive Bayes classifiers.

PubMed

Klement, William; Wilk, Szymon; Michalowski, Wojtek; Farion, Ken J; Osmond, Martin H; Verter, Vedat

2012-03-01

Using an automatic data-driven approach, this paper develops a prediction model that achieves more balanced performance (in terms of sensitivity and specificity) than the Canadian Assessment of Tomography for Childhood Head Injury (CATCH) rule, when predicting the need for computed tomography (CT) imaging of children after a minor head injury. CT is widely considered an effective tool for evaluating patients with minor head trauma who have potentially suffered serious intracranial injury. However, its use poses possible harmful effects, particularly for children, due to exposure to radiation. Safety concerns, along with issues of cost and practice variability, have led to calls for the development of effective methods to decide when CT imaging is needed. Clinical decision rules represent such methods and are normally derived from the analysis of large prospectively collected patient data sets. The CATCH rule was created by a group of Canadian pediatric emergency physicians to support the decision of referring children with minor head injury to CT imaging. The goal of the CATCH rule was to maximize the sensitivity of predictions of potential intracranial lesion while keeping specificity at a reasonable level. After extensive analysis of the CATCH data set, characterized by severe class imbalance, and after a thorough evaluation of several data mining methods, we derived an ensemble of multiple Naive Bayes classifiers as the prediction model for CT imaging decisions. In the first phase of the experiment we compared the proposed ensemble model to other ensemble models employing rule-, tree- and instance-based member classifiers. Our prediction model demonstrated the best performance in terms of AUC, G-mean and sensitivity measures. In the second phase, using a bootstrapping experiment similar to that reported by the CATCH investigators, we showed that the proposed ensemble model achieved a more balanced predictive performance than the CATCH rule with an average sensitivity of 82.8% and an average specificity of 74.4% (vs. 98.1% and 50.0% for the CATCH rule respectively). Automatically derived prediction models cannot replace a physician's acumen. However, they help establish reference performance indicators for the purpose of developing clinical decision rules so the trade-off between prediction sensitivity and specificity is better understood. Copyright © 2011 Elsevier B.V. All rights reserved.

Decorrelation-based viscosity measurement using phase-sensitive optical coherence tomography (Conference Presentation)

NASA Astrophysics Data System (ADS)

Blackburn, Brecken J.; Gu, Shi; Jenkins, Michael W.; Rollins, Andrew M.

2017-02-01

A robust method to measure viscosity of microquantities of biological samples, such as blood and mucus, could lead to a better understanding and diagnosis of diseases. Microsamples have presented persistent challenges to conventional rheology, which requires bulk quantities of a sample. Alternatively, fluid viscosity can be probed by monitoring microscale motion of particles. Here, we present a decorrelation-based method using M-mode phase-sensitive optical coherence tomography (OCT) to measure particle Brownian motion. This is similar to previous methods using laser speckle decorrelation but with sensitivity to nanometer-scale displacement. This allows for the measurement of decorrelation in less than 1 millisecond and significantly decreases sensitivity to bulk motion, thereby potentially enabling in vivo and in situ applications. From first principles, an analytical method is established using M-mode images obtained from a 47 kHz spectral-domain OCT system. A g(1) first-order autocorrelation is calculated from windows containing several pixels over a time frame of 200-1000 microseconds. Total imaging time is 500 milliseconds for averaging purposes. The autocorrelation coefficient over this short time frame decreases linearly and at a rate proportional to the diffusion constant of the particles, allowing viscosity to be calculated. In verification experiments using phantoms of microbeads in 200 µL glycerol-water mixtures, this method showed insensitivity to 2 mm/s lateral bulk motion and accurate viscosity measurements over a depth of 400 µm. In addition, the method measured a significant decrease of the apparent diffusion constant of soft tissue after formalin fixation, suggesting potential applications in mapping tissue stiffness.

Highly sensitive time-resolved thermography and multivariate image analysis of the cerebral cortex for intrasurgical diagnostics

NASA Astrophysics Data System (ADS)

Hollmach, Julia; Hoffmann, Nico; Schnabel, Christian; Küchler, Saskia; Sobottka, Stephan; Kirsch, Matthias; Schackert, Gabriele; Koch, Edmund; Steiner, Gerald

2013-03-01

Time-resolved thermography is a novel method to assess thermal variations and heterogeneities in tissue and blood. The recent generation of thermal cameras provides a sensitivity of less than mK. This high sensitivity in conjunction with non-invasive, label-free and radiation-free monitoring makes thermography a promising tool for intrasurgical diagnostics. In brain surgery, time-resolved thermography can be employed to distinguish between normal and anomalous tissue. In this study, we investigated and discussed the potential of time-resolved thermography in neurosurgery for the intraoperative detection and demarcation of tumor borders. Algorithms for segmentation, reduction of movement artifacts and image fusion were developed. The preprocessed image stacks were subjected to discrete wavelet transform to examine individual frequency components. K-means clustering was used for image evaluation to reveal similarities within the image sequence. The image evaluation shows significant differences for both types of tissue. Tumor and normal tissues have different time characteristics in heat production and transfer. Furthermore, tumor could be highlighted. These results demonstrate that time-resolved thermography is able to support the detection of tumors in a contactless manner without any side effects for the tissue. The intraoperative usage of time-resolved thermography improves the accuracy of tumor resections to prevent irreversible brain damage during surgery.

Comparisons between conventional optical imaging and parametric indirect microscopic imaging on human skin detection

NASA Astrophysics Data System (ADS)

Liu, Guoyan; Gao, Kun; Liu, Xuefeng; Ni, Guoqiang

2016-10-01

We report a new method, polarization parameters indirect microscopic imaging with a high transmission infrared light source, to detect the morphology and component of human skin. A conventional reflection microscopic system is used as the basic optical system, into which a polarization-modulation mechanics is inserted and a high transmission infrared light source is utilized. The near-field structural characteristics of human skin can be delivered by infrared waves and material coupling. According to coupling and conduction physics, changes of the optical wave parameters can be calculated and curves of the intensity of the image can be obtained. By analyzing the near-field polarization parameters in nanoscale, we can finally get the inversion images of human skin. Compared with the conventional direct optical microscope, this method can break diffraction limit and achieve a super resolution of sub-100nm. Besides, the method is more sensitive to the edges, wrinkles, boundaries and impurity particles.

Smart phone: a popular device supports amylase activity assay in fisheries research.

PubMed

Thongprajukaew, Karun; Choodum, Aree; Sa-E, Barunee; Hayee, Ummah

2014-11-15

Colourimetric determinations of amylase activity were developed based on a standard dinitrosalicylic acid (DNS) staining method, using maltose as the analyte. Intensities and absorbances of red, green and blue (RGB) were obtained with iPhone imaging and Adobe Photoshop image analysis. Correlation of green and analyte concentrations was highly significant, and the accuracy of the developed method was excellent in analytical performance. The common iPhone has sufficient imaging ability for accurate quantification of maltose concentrations. Detection limits, sensitivity and linearity were comparable to a spectrophotometric method, but provided better inter-day precision. In quantifying amylase specific activity from a commercial source (P>0.02) and fish samples (P>0.05), differences compared with spectrophotometric measurements were not significant. We have demonstrated that iPhone imaging with image analysis in Adobe Photoshop has potential for field and laboratory studies of amylase. Copyright © 2014 Elsevier Ltd. All rights reserved.

Automatic patient-adaptive bleeding detection in a capsule endoscopy

NASA Astrophysics Data System (ADS)

Jung, Yun Sub; Kim, Yong Ho; Lee, Dong Ha; Lee, Sang Ho; Song, Jeong Joo; Kim, Jong Hyo

2009-02-01

We present a method for patient-adaptive detection of bleeding region for a Capsule Endoscopy (CE) images. The CE system has 320x320 resolution and transmits 3 images per second to receiver during around 10-hour. We have developed a technique to detect the bleeding automatically utilizing color spectrum transformation (CST) method. However, because of irregular conditions like organ difference, patient difference and illumination condition, detection performance is not uniform. To solve this problem, the detection method in this paper include parameter compensation step which compensate irregular image condition using color balance index (CBI). We have investigated color balance through sequential 2 millions images. Based on this pre-experimental result, we defined ΔCBI to represent deviate of color balance compared with standard small bowel color balance. The ΔCBI feature value is extracted from each image and used in CST method as parameter compensation constant. After candidate pixels were detected using CST method, they were labeled and examined with a bleeding character. We tested our method with 4,800 images in 12 patient data set (9 abnormal, 3 normal). Our experimental results show the proposed method achieves (before patient adaptive method : 80.87% and 74.25%, after patient adaptive method : 94.87% and 96.12%) of sensitivity and specificity.

Polarization sensitive optical coherence tomography – a review [Invited

PubMed Central

de Boer, Johannes F.; Hitzenberger, Christoph K.; Yasuno, Yoshiaki

2017-01-01

Optical coherence tomography (OCT) is now a well-established modality for high-resolution cross-sectional and three-dimensional imaging of transparent and translucent samples and tissues. Conventional, intensity based OCT, however, does not provide a tissue-specific contrast, causing an ambiguity with image interpretation in several cases. Polarization sensitive (PS) OCT draws advantage from the fact that several materials and tissues can change the light’s polarization state, adding an additional contrast channel and providing quantitative information. In this paper, we review basic and advanced methods of PS-OCT and demonstrate its use in selected biomedical applications. PMID:28663869

Performance Sensitivity Studies on the PIAA Implementation of the High-Contrast Imaging Testbed

NASA Technical Reports Server (NTRS)

Sidick, Erkin; Lou, John; Shaklan, Stuart; Levine, Marie

2010-01-01

This slide presentation reviews the sensitivity studies on the Phase-Induced Amplitude Apodization (PIAA), or pupil mapping using the High-Contrast Imaging Testbed (HCIT). PIAA is a promising technique in high-dynamic range stellar coronagraph. This presentation reports on the investigation of the effects of the phase and rigid-body errors of various optics on the narrowband contrast performance of the PIAA/HCIT hybrid system. The results have shown that the 2-step wavefront control method utilizing 2-DMs is quite effective in compensating the effects of realistic phase and rigid-body errors of various optics

Optical tomographic imaging for breast cancer detection

NASA Astrophysics Data System (ADS)

Cong, Wenxiang; Intes, Xavier; Wang, Ge

2017-09-01

Diffuse optical breast imaging utilizes near-infrared (NIR) light propagation through tissues to assess the optical properties of tissues for the identification of abnormal tissue. This optical imaging approach is sensitive, cost-effective, and does not involve any ionizing radiation. However, the image reconstruction of diffuse optical tomography (DOT) is a nonlinear inverse problem and suffers from severe illposedness due to data noise, NIR light scattering, and measurement incompleteness. An image reconstruction method is proposed for the detection of breast cancer. This method splits the image reconstruction problem into the localization of abnormal tissues and quantification of absorption variations. The localization of abnormal tissues is performed based on a well-posed optimization model, which can be solved via a differential evolution optimization method to achieve a stable reconstruction. The quantification of abnormal absorption is then determined in localized regions of relatively small extents, in which a potential tumor might be. Consequently, the number of unknown absorption variables can be greatly reduced to overcome the underdetermined nature of DOT. Numerical simulation experiments are performed to verify merits of the proposed method, and the results show that the image reconstruction method is stable and accurate for the identification of abnormal tissues, and robust against the measurement noise of data.

Detection theory for accurate and non-invasive skin cancer diagnosis using dynamic thermal imaging

PubMed Central

Godoy, Sebastián E.; Hayat, Majeed M.; Ramirez, David A.; Myers, Stephen A.; Padilla, R. Steven; Krishna, Sanjay

2017-01-01

Skin cancer is the most common cancer in the United States with over 3.5M annual cases. Presently, visual inspection by a dermatologist has good sensitivity (> 90%) but poor specificity (< 10%), especially for melanoma, which leads to a high number of unnecessary biopsies. Here we use dynamic thermal imaging (DTI) to demonstrate a rapid, accurate and non-invasive imaging system for detection of skin cancer. In DTI, the lesion is cooled down and the thermal recovery is recorded using infrared imaging. The thermal recovery curves of the suspected lesions are then utilized in the context of continuous-time detection theory in order to define an optimal statistical decision rule such that the sensitivity of the algorithm is guaranteed to be at a maximum for every prescribed false-alarm probability. The proposed methodology was tested in a pilot study including 140 human subjects demonstrating a sensitivity in excess of 99% for a prescribed specificity in excess of 99% for detection of skin cancer. To the best of our knowledge, this is the highest reported accuracy for any non-invasive skin cancer diagnosis method. PMID:28736673

Quantitative evaluation of skeletal muscle defects in second harmonic generation images.

PubMed

Liu, Wenhua; Raben, Nina; Ralston, Evelyn

2013-02-01

Skeletal muscle pathologies cause irregularities in the normally periodic organization of the myofibrils. Objective grading of muscle morphology is necessary to assess muscle health, compare biopsies, and evaluate treatments and the evolution of disease. To facilitate such quantitation, we have developed a fast, sensitive, automatic imaging analysis software. It detects major and minor morphological changes by combining texture features and Fourier transform (FT) techniques. We apply this tool to second harmonic generation (SHG) images of muscle fibers which visualize the repeating myosin bands. Texture features are then calculated by using a Haralick gray-level cooccurrence matrix in MATLAB. Two scores are retrieved from the texture correlation plot by using FT and curve-fitting methods. The sensitivity of the technique was tested on SHG images of human adult and infant muscle biopsies and of mouse muscle samples. The scores are strongly correlated to muscle fiber condition. We named the software MARS (muscle assessment and rating scores). It is executed automatically and is highly sensitive even to subtle defects. We propose MARS as a powerful and unbiased tool to assess muscle health.

Quantitative evaluation of skeletal muscle defects in second harmonic generation images

NASA Astrophysics Data System (ADS)

Liu, Wenhua; Raben, Nina; Ralston, Evelyn

2013-02-01

Skeletal muscle pathologies cause irregularities in the normally periodic organization of the myofibrils. Objective grading of muscle morphology is necessary to assess muscle health, compare biopsies, and evaluate treatments and the evolution of disease. To facilitate such quantitation, we have developed a fast, sensitive, automatic imaging analysis software. It detects major and minor morphological changes by combining texture features and Fourier transform (FT) techniques. We apply this tool to second harmonic generation (SHG) images of muscle fibers which visualize the repeating myosin bands. Texture features are then calculated by using a Haralick gray-level cooccurrence matrix in MATLAB. Two scores are retrieved from the texture correlation plot by using FT and curve-fitting methods. The sensitivity of the technique was tested on SHG images of human adult and infant muscle biopsies and of mouse muscle samples. The scores are strongly correlated to muscle fiber condition. We named the software MARS (muscle assessment and rating scores). It is executed automatically and is highly sensitive even to subtle defects. We propose MARS as a powerful and unbiased tool to assess muscle health.

Retina lesion and microaneurysm segmentation using morphological reconstruction methods with ground-truth data.

PubMed

Karnowski, Thomas P; Govindasamy, V; Tobin, Kenneth W; Chaum, Edward; Abramoff, M D

2008-01-01

In this work we report on a method for lesion segmentation based on the morphological reconstruction methods of Sbeh et. al. We adapt the method to include segmentation of dark lesions with a given vasculature segmentation. The segmentation is performed at a variety of scales determined using ground-truth data. Since the method tends to over-segment imagery, ground-truth data was used to create post-processing filters to separate nuisance blobs from true lesions. A sensitivity and specificity of 90% of classification of blobs into nuisance and actual lesion was achieved on two data sets of 86 images and 1296 images.

Automatic Stem Cell Detection in Microscopic Whole Mouse Cryo-imaging

PubMed Central

Wuttisarnwattana, Patiwet; Gargesha, Madhusudhana; Hof, Wouter van’t; Cooke, Kenneth R.

2016-01-01

With its single cell sensitivity over volumes as large as or larger than a mouse, cryo-imaging enables imaging of stem cell biodistribution, homing, engraftment, and molecular mechanisms. We developed and evaluated a highly automated software tool to detect fluorescently labeled stem cells within very large (~200GB) cryo-imaging datasets. Cell detection steps are: preprocess, remove immaterial regions, spatially filter to create features, identify candidate pixels, classify pixels using bagging decision trees, segment cell patches, and perform 3D labeling. There are options for analysis and visualization. To train the classifier, we created synthetic images by placing realistic digital cell models onto cryo-images of control mice devoid of cells. Very good cell detection results were (precision=98.49%, recall=99.97%) for synthetic cryo-images, (precision=97.81%, recall=97.71%) for manually evaluated, actual cryo-images, and <1% false positives in control mice. An α-multiplier applied to features allows one to correct for experimental variations in cell brightness due to labeling. On dim cells (37% of standard brightness), with correction, we improved recall (49.26%→99.36%) without a significant drop in precision (99.99%→99.75%). With tail vein injection, multipotent adult progenitor cells in a graft-versus-host-disease model in the first days post injection were predominantly found in lung, liver, spleen, and bone marrow. Distribution was not simply related to blood flow. The lung contained clusters of cells while other tissues contained single cells. Our methods provided stem cell distribution anywhere in mouse with single cell sensitivity. Methods should provide a rational means of evaluating dosing, delivery methods, cell enhancements, and mechanisms for therapeutic cells. PMID:26552080

Direct Imaging of Radionuclide-Produced Electrons and Positrons with an Ultrathin Phosphor

PubMed Central

Chen, Liying; Gobar, Lisa S.; Knowles, Negar G.; Liu, Zhonglin; Gmitro, Arthur F.; Barrett, Harrison H.

2008-01-01

Current electron detectors are either unable to image in vivo or lack sufficient spatial resolution because of electron scattering in thick detector materials. This study was aimed at developing a sensitive high-resolution system capable of detecting electron-emitting isotopes in vivo. Methods The system uses a lens-coupled charge-coupled-device camera to capture the scintillation light excited by an electron-emitting object near an ultrathin phosphor. The spatial resolution and sensitivity of the system were measured with a 3.7-kBq 90Y/90Sr β-source and a 70-µm resin bead labeled with 99mTc. Finally, we imaged the 99mTc-pertechnetate concentration in the mandibular gland of a mouse in vivo. Results Useful images were obtained with only a few hundred emitted β particles from the 90Y/90Sr source or conversion electrons from the 99mTc bead source. The in vivo image showed a clear profile of the mandibular gland and many fine details with exposures of as low as 30 s. All measurements were consistent with a spatial resolution of about 50 µm, corresponding to 2.5 detector pixels with the current camera. Conclusion Our new electron-imaging system can image electron-emitting isotope distributions at high resolution and sensitivity. The system is useful for in vivo imaging of small animals and small, exposed regions on humans. The ability to image β particles, positrons, and conversion electrons makes the system applicable to most isotopes. PMID:18552136

Bone images from dual-energy subtraction chest radiography in the detection of rib fractures.

PubMed

Szucs-Farkas, Zsolt; Lautenschlager, Katrin; Flach, Patricia M; Ott, Daniel; Strautz, Tamara; Vock, Peter; Ruder, Thomas D

2011-08-01

To assess the sensitivity and image quality of chest radiography (CXR) with or without dual-energy subtracted (ES) bone images in the detection of rib fractures. In this retrospective study, 39 patients with 204 rib fractures and 24 subjects with no fractures were examined with a single exposure dual-energy subtraction digital radiography system. Three blinded readers first evaluated the non-subtracted posteroanterior and lateral chest radiographs alone, and 3 months later they evaluated the non-subtracted images together with the subtracted posteroanterior bone images. The locations of rib fractures were registered with confidence levels on a 3-grade scale. Image quality was rated on a 5-point scale. Marks by readers were compared with fracture localizations in CT as a standard of reference. The sensivity for fracture detection using both methods was very similar (34.3% with standard CXR and 33.5% with ES-CXR, p=0.92). At the patient level, both sensitivity (71.8%) and specificity (92.9%) with or without ES were identical. Diagnostic confidence was not significantly different (2.61 with CXR and 2.75 with ES-CXR, p=0.063). Image quality with ES was rated higher than that on standard CXR (4.08 vs. 3.74, p<0.001). Despite a better image quality, adding ES bone images to standard radiographs of the chest does not provide better sensitivity or improved diagnostic confidence in the detection of rib fractures. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Synthetic Minority Oversampling Technique and Fractal Dimension for Identifying Multiple Sclerosis

NASA Astrophysics Data System (ADS)

Zhang, Yu-Dong; Zhang, Yin; Phillips, Preetha; Dong, Zhengchao; Wang, Shuihua

Multiple sclerosis (MS) is a severe brain disease. Early detection can provide timely treatment. Fractal dimension can provide statistical index of pattern changes with scale at a given brain image. In this study, our team used susceptibility weighted imaging technique to obtain 676 MS slices and 880 healthy slices. We used synthetic minority oversampling technique to process the unbalanced dataset. Then, we used Canny edge detector to extract distinguishing edges. The Minkowski-Bouligand dimension was a fractal dimension estimation method and used to extract features from edges. Single hidden layer neural network was used as the classifier. Finally, we proposed a three-segment representation biogeography-based optimization to train the classifier. Our method achieved a sensitivity of 97.78±1.29%, a specificity of 97.82±1.60% and an accuracy of 97.80±1.40%. The proposed method is superior to seven state-of-the-art methods in terms of sensitivity and accuracy.

Probing myocardium biomechanics using quantitative optical coherence elastography

NASA Astrophysics Data System (ADS)

Wang, Shang; Lopez, Andrew L.; Morikawa, Yuka; Tao, Ge; Li, Jiasong; Larina, Irina V.; Martin, James F.; Larin, Kirill V.

2015-03-01

We present a quantitative optical coherence elastographic method for noncontact assessment of the myocardium elasticity. The method is based on shear wave imaging optical coherence tomography (SWI-OCT), where a focused air-puff system is used to induce localized tissue deformation through a low-pressure short-duration air stream and a phase-sensitive OCT system is utilized to monitor the propagation of the induced tissue displacement with nanoscale sensitivity. The 1-D scanning of M-mode OCT imaging and the application of optical phase retrieval and mapping techniques enable the reconstruction and visualization of 2-D depth-resolved shear wave propagation in tissue with ultra-high frame rate. The feasibility of this method in quantitative elasticity measurement is demonstrated on tissue-mimicking phantoms with the estimated Young's modulus compared with uniaxial compression tests. We also performed pilot experiments on ex vivo mouse cardiac muscle tissues with normal and genetically altered cardiomyocytes. Our results indicate this noncontact quantitative optical coherence elastographic method can be a useful tool for the cardiac muscle research and studies.

Incorporate Imaging Characteristics Into an Arteriovenous Malformation Radiosurgery Plan Evaluation Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang Pengpeng; Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, NY; Wu, Leester

Purpose: To integrate imaging performance characteristics, specifically sensitivity and specificity, of magnetic resonance angiography (MRA) and digital subtraction angiography (DSA) into arteriovenous malformation (AVM) radiosurgery planning and evaluation. Methods and Materials: Images of 10 patients with AVMs located in critical brain areas were analyzed in this retrospective planning study. The image findings were first used to estimate the sensitivity and specificity of MRA and DSA. Instead of accepting the imaging observation as a binary (yes or no) mapping of AVM location, our alternative is to translate the image into an AVM probability distribution map by incorporating imagers' sensitivity and specificity,more » and to use this map as a basis for planning and evaluation. Three sets of radiosurgery plans, targeting the MRA and DSA positive overlap, MRA positive, and DSA positive were optimized for best conformality. The AVM obliteration rate (ORAVM) and brain complication rate served as endpoints for plan comparison. Results: In our 10-patient study, the specificities and sensitivities of MRA and DSA were estimated to be (0.95, 0.74) and (0.71, 0.95), respectively. The positive overlap of MRA and DSA accounted for 67.8% {+-} 4.9% of the estimated true AVM volume. Compared with plans targeting MRA and DSA-positive overlap, plans targeting MRA-positive or DSA-positive improved ORAVM by 4.1% {+-} 1.9% and 15.7% {+-} 8.3%, while also increasing the complication rate by 1.0% {+-} 0.8% and 4.4% {+-} 2.3%, respectively. Conclusions: The impact of imagers' quality should be quantified and incorporated in AVM radiosurgery planning and evaluation to facilitate clinical decision making.« less

Effects of coupling between the vibrational modes on CARS signal

NASA Astrophysics Data System (ADS)

Patel, Vishesha; Malinovskaya, Svetlana

2007-06-01

CARS is well suited spectroscopy method for imaging specific molecules, e.g., proteins and live cells, diagnosis of cancerous cells, imaging dueterated compounds, etc. CARS imaging techniques avoid problems associated with photo bleaching and photo induced toxicity. The CARS signal is accompanied by a strong non resonant background which may overshadow the weak signal of interest. Two methods, using femtosecond chriped laser pulses and providing the Rabi oscillation and the adiabatic passage type of control [1], allow one to achieve sensitivity with high resolution and are known to efficiently suppress background. It has been previously shown that coupling between vibrational modes affects the sensitivity of the Raman signal and selective excitation of vibrational modes [2]. In this paper we will discuss simulation results on vibrational coupling between modes and its impact into control mechanisms of the CARS signal. [1] S.A.Malinovskaya, Physical.Rev.A 73, 033416(2006) [2] S.A. Malinovskaya,P.H. Bucksbaum, and P.R. Berman, J. Chem. Phys. 121, 3434 (2004).

Comparison of different methods for estimating snowcover in forested, mountainous basins using LANDSAT (ERTS) images. [Washington and Santiam River, Oregon

NASA Technical Reports Server (NTRS)

Meier, M. J.; Evans, W. E.

1975-01-01

Snow-covered areas on LANDSAT (ERTS) images of the Santiam River basin, Oregon, and other basins in Washington were measured using several operators and methods. Seven methods were used: (1) Snowline tracing followed by measurement with planimeter, (2) mean snowline altitudes determined from many locations, (3) estimates in 2.5 x 2.5 km boxes of snow-covered area with reference to snow-free images, (4) single radiance-threshold level for entire basin, (5) radiance-threshold setting locally edited by reference to altitude contours and other images, (6) two-band color-sensitive extraction locally edited as in (5), and (7) digital (spectral) pattern recognition techniques. The seven methods are compared in regard to speed of measurement, precision, the ability to recognize snow in deep shadow or in trees, relative cost, and whether useful supplemental data are produced.

Obtaining the phase in the star test using genetic algorithms

NASA Astrophysics Data System (ADS)

Salazar Romero, Marcos A.; Vazquez-Montiel, Sergio; Cornejo-Rodriguez, Alejandro

2004-10-01

The star test is conceptually perhaps the most basic and simplest of all methods of testing image-forming optical systems, the irradiance distribution at the image of a point source (such as a star) is give for the Point Spread Function, PSF. The PSF is very sensitive to aberrations. One way to quantify the PSF is measuring the irradiance distribution on the image of the source point. On the other hand, if we know the aberrations introduced by the optical systems and utilizing the diffraction theory then we can calculate the PSF. In this work we propose a method in order to find the wavefront aberrations starting from the PSF, transforming the problem of fitting a polynomial of aberrations in a problem of optimization using Genetic Algorithm. Also, we show that this method is immune to the noise introduced in the register or recording of the image. Results of these methods are shown.

Two-Layer Fragile Watermarking Method Secured with Chaotic Map for Authentication of Digital Holy Quran

PubMed Central

Khalil, Mohammed S.; Khan, Muhammad Khurram; Alginahi, Yasser M.

2014-01-01

This paper presents a novel watermarking method to facilitate the authentication and detection of the image forgery on the Quran images. Two layers of embedding scheme on wavelet and spatial domain are introduced to enhance the sensitivity of fragile watermarking and defend the attacks. Discrete wavelet transforms are applied to decompose the host image into wavelet prior to embedding the watermark in the wavelet domain. The watermarked wavelet coefficient is inverted back to spatial domain then the least significant bits is utilized to hide another watermark. A chaotic map is utilized to blur the watermark to make it secure against the local attack. The proposed method allows high watermark payloads, while preserving good image quality. Experiment results confirm that the proposed methods are fragile and have superior tampering detection even though the tampered area is very small. PMID:25028681

Two-layer fragile watermarking method secured with chaotic map for authentication of digital Holy Quran.

PubMed

Khalil, Mohammed S; Kurniawan, Fajri; Khan, Muhammad Khurram; Alginahi, Yasser M

2014-01-01

This paper presents a novel watermarking method to facilitate the authentication and detection of the image forgery on the Quran images. Two layers of embedding scheme on wavelet and spatial domain are introduced to enhance the sensitivity of fragile watermarking and defend the attacks. Discrete wavelet transforms are applied to decompose the host image into wavelet prior to embedding the watermark in the wavelet domain. The watermarked wavelet coefficient is inverted back to spatial domain then the least significant bits is utilized to hide another watermark. A chaotic map is utilized to blur the watermark to make it secure against the local attack. The proposed method allows high watermark payloads, while preserving good image quality. Experiment results confirm that the proposed methods are fragile and have superior tampering detection even though the tampered area is very small.

A new blood vessel extraction technique using edge enhancement and object classification.

PubMed

Badsha, Shahriar; Reza, Ahmed Wasif; Tan, Kim Geok; Dimyati, Kaharudin

2013-12-01

Diabetic retinopathy (DR) is increasing progressively pushing the demand of automatic extraction and classification of severity of diseases. Blood vessel extraction from the fundus image is a vital and challenging task. Therefore, this paper presents a new, computationally simple, and automatic method to extract the retinal blood vessel. The proposed method comprises several basic image processing techniques, namely edge enhancement by standard template, noise removal, thresholding, morphological operation, and object classification. The proposed method has been tested on a set of retinal images. The retinal images were collected from the DRIVE database and we have employed robust performance analysis to evaluate the accuracy. The results obtained from this study reveal that the proposed method offers an average accuracy of about 97 %, sensitivity of 99 %, specificity of 86 %, and predictive value of 98 %, which is superior to various well-known techniques.

Image guided versus palpation guided core needle biopsy of palpable breast masses: a prospective study

PubMed Central

Hari, Smriti; Kumari, Swati; Srivastava, Anurag; Thulkar, Sanjay; Mathur, Sandeep; Veedu, Prasad Thotton

2016-01-01

Background & objectives: Biopsy of palpable breast masses can be performed manually by palpation guidance or under imaging guidance. Based on retrospective studies, image guided biopsy is considered more accurate than palpation guided breast biopsy; however, these techniques have not been compared prospectively. We conducted this prospective study to verify the superiority and determine the size of beneficial effect of image guided biopsy over palpation guided biopsy. Methods: Over a period of 18 months, 36 patients each with palpable breast masses were randomized into palpation guided and image guided breast biopsy arms. Ultrasound was used for image guidance in 33 patients and mammographic (stereotactic) guidance in three patients. All biopsies were performed using 14 gauge automated core biopsy needles. Inconclusive, suspicious or imaging-histologic discordant biopsies were repeated. Results: Malignancy was found in 30 of 36 women in palpation guided biopsy arm and 27 of 36 women in image guided biopsy arm. Palpation guided biopsy had sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of 46.7, 100, 100, 27.3 per cent, respectively, for diagnosing breast cancer. Nineteen of 36 women (52.8%) required repeat biopsy because of inadequate samples (7 of 19), suspicious findings (2 of 19) or imaging-histologic discordance (10 of 19). On repeat biopsy, malignancy was found in all cases of imaging-histologic discordance. Image guided biopsy had 96.3 per cent sensitivity and 100 per cent specificity. There was no case of inadequate sample or imaging-histologic discordance with image guided biopsy. Interpretation & conclusions: Our results showed that in palpable breast masses, image guided biopsy was superior to palpation guided biopsy in terms of sensitivity, false negative rate and repeat biopsy rates. PMID:27488003

Fully Automated Segmentation of Fluid/Cyst Regions in Optical Coherence Tomography Images With Diabetic Macular Edema Using Neutrosophic Sets and Graph Algorithms.

PubMed

Rashno, Abdolreza; Koozekanani, Dara D; Drayna, Paul M; Nazari, Behzad; Sadri, Saeed; Rabbani, Hossein; Parhi, Keshab K

2018-05-01

This paper presents a fully automated algorithm to segment fluid-associated (fluid-filled) and cyst regions in optical coherence tomography (OCT) retina images of subjects with diabetic macular edema. The OCT image is segmented using a novel neutrosophic transformation and a graph-based shortest path method. In neutrosophic domain, an image is transformed into three sets: (true), (indeterminate) that represents noise, and (false). This paper makes four key contributions. First, a new method is introduced to compute the indeterminacy set , and a new -correction operation is introduced to compute the set in neutrosophic domain. Second, a graph shortest-path method is applied in neutrosophic domain to segment the inner limiting membrane and the retinal pigment epithelium as regions of interest (ROI) and outer plexiform layer and inner segment myeloid as middle layers using a novel definition of the edge weights . Third, a new cost function for cluster-based fluid/cyst segmentation in ROI is presented which also includes a novel approach in estimating the number of clusters in an automated manner. Fourth, the final fluid regions are achieved by ignoring very small regions and the regions between middle layers. The proposed method is evaluated using two publicly available datasets: Duke, Optima, and a third local dataset from the UMN clinic which is available online. The proposed algorithm outperforms the previously proposed Duke algorithm by 8% with respect to the dice coefficient and by 5% with respect to precision on the Duke dataset, while achieving about the same sensitivity. Also, the proposed algorithm outperforms a prior method for Optima dataset by 6%, 22%, and 23% with respect to the dice coefficient, sensitivity, and precision, respectively. Finally, the proposed algorithm also achieves sensitivity of 67.3%, 88.8%, and 76.7%, for the Duke, Optima, and the university of minnesota (UMN) datasets, respectively.

Discrimination between weaned and unweaned Atlantic cod (Gadus morhua) in capture-based aquaculture (CBA) by X-ray imaging and radio-frequency metal detector.

PubMed

Misimi, Ekrem; Martinsen, Svein; Mathiassen, John Reidar; Erikson, Ulf

2014-01-01

The aim of this study was to investigate the feasibility of two detection methods for use in discrimination and sorting of adult Atlantic cod (about 2 kg) in the small scale capture-based aquaculture (CBA). Presently, there is no established method for discrimination of weaned and unweaned cod in CBA. Generally, 60-70% of the wild-caught cod in the CBA are weaned into commercial dry feed. To increase profitability for the fish farmers, unweaned cod must be separated from the stock, meaning the fish must be sorted into two groups - unweaned and weaned from moist feed. The challenges with handling of large numbers of fish in cages, defined the limits of the applied technology. As a result, a working model was established, focusing on implementing different marking materials added to the fish feed, and different technology for detecting the feed presence in the fish gut. X-ray imaging in two modes (planar and dual energy band) and sensitive radio-frequency metal detection were the detection methods that were chosen for the investigations. Both methods were tested in laboratory conditions using dead fish with marked feed inserted into the gut cavity. In particular, the sensitive radio-frequency metal detection method with carbonyl powder showed very promising results in detection of marked feed. Results show also that Dual energy band X-ray imaging may have potential for prediction of fat content in the feed. Based on the investigations it can be concluded that both X-ray imaging and sensitive radio-frequency metal detector technology have the potential for detecting cod having consumed marked feed. These are all technologies that may be adapted to large scale handling of fish from fish cages. Thus, it may be possible to discriminate between unweaned and weaned cod in a large scale grading situation. Based on the results of this study, a suggestion for evaluation of concept for in-situ sorting system is presented.

Ultrahigh resolution radiation imaging system using an optical fiber structure scintillator plate.

PubMed

Yamamoto, Seiichi; Kamada, Kei; Yoshikawa, Akira

2018-02-16

High resolution imaging of radiation is required for such radioisotope distribution measurements as alpha particle detection in nuclear facilities or high energy physics experiments. For this purpose, we developed an ultrahigh resolution radiation imaging system using an optical fiber structure scintillator plate. We used a ~1-μm diameter fiber structured GdAlO 3 :Ce (GAP) /α-Al 2 O 3 scintillator plate to reduce the light spread. The fiber structured scintillator plate was optically coupled to a tapered optical fiber plate to magnify the image and combined with a lens-based high sensitivity CCD camera. We observed the images of alpha particles with a spatial resolution of ~25 μm. For the beta particles, the images had various shapes, and the trajectories of the electrons were clearly observed in the images. For the gamma photons, the images also had various shapes, and the trajectories of the secondary electrons were observed in some of the images. These results show that combining an optical fiber structure scintillator plate with a tapered optical fiber plate and a high sensitivity CCD camera achieved ultrahigh resolution and is a promising method to observe the images of the interactions of radiation in a scintillator.

Intraoperative Imaging Guidance for Sentinel Node Biopsy in Melanoma Using a Mobile Gamma Camera

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dengel, Lynn T; Judy, Patricia G; Petroni, Gina R

2011-04-01

The objective is to evaluate the sensitivity and clinical utility of intraoperative mobile gamma camera (MGC) imaging in sentinel lymph node biopsy (SLNB) in melanoma. The false-negative rate for SLNB for melanoma is approximately 17%, for which failure to identify the sentinel lymph node (SLN) is a major cause. Intraoperative imaging may aid in detection of SLN near the primary site, in ambiguous locations, and after excision of each SLN. The present pilot study reports outcomes with a prototype MGC designed for rapid intraoperative image acquisition. We hypothesized that intraoperative use of the MGC would be feasible and that sensitivitymore » would be at least 90%. From April to September 2008, 20 patients underwent Tc99 sulfur colloid lymphoscintigraphy, and SLNB was performed with use of a conventional fixed gamma camera (FGC), and gamma probe followed by intraoperative MGC imaging. Sensitivity was calculated for each detection method. Intraoperative logistical challenges were scored. Cases in which MGC provided clinical benefit were recorded. Sensitivity for detecting SLN basins was 97% for the FGC and 90% for the MGC. A total of 46 SLN were identified: 32 (70%) were identified as distinct hot spots by preoperative FGC imaging, 31 (67%) by preoperative MGC imaging, and 43 (93%) by MGC imaging pre- or intraoperatively. The gamma probe identified 44 (96%) independent of MGC imaging. The MGC provided defined clinical benefit as an addition to standard practice in 5 (25%) of 20 patients. Mean score for MGC logistic feasibility was 2 on a scale of 1-9 (1 = best). Intraoperative MGC imaging provides additional information when standard techniques fail or are ambiguous. Sensitivity is 90% and can be increased. This pilot study has identified ways to improve the usefulness of an MGC for intraoperative imaging, which holds promise for reducing false negatives of SLNB for melanoma.« less

Imaging for Appendicitis: Should Radiation-induced Cancer Risks Affect Modality Selection?

PubMed Central

Kiatpongsan, Sorapop; Meng, Lesley; Eisenberg, Jonathan D.; Herring, Maurice; Avery, Laura L.; Kong, Chung Yin

2014-01-01

Purpose To compare life expectancy (LE) losses attributable to three imaging strategies for appendicitis in adults—computed tomography (CT), ultrasonography (US) followed by CT for negative or indeterminate US results, and magnetic resonance (MR) imaging—by using a decision-analytic model. Materials and Methods In this model, for each imaging strategy, LE losses for 20-, 40-, and 65-year-old men and women were computed as a function of five key variables: baseline cohort LE, test performance, surgical mortality, risk of death from delayed diagnosis (missed appendicitis), and LE loss attributable to radiation-induced cancer death. Appendicitis prevalence, test performance, mortality rates from surgery and missed appendicitis, and radiation doses from CT were elicited from the published literature and institutional data. LE loss attributable to radiation exposure was projected by using a separate organ-specific model that accounted for anatomic coverage during a typical abdominopelvic CT examination. One- and two-way sensitivity analyses were performed to evaluate effects of model input variability on results. Results Outcomes across imaging strategies differed minimally—for example, for 20-year-old men, corresponding LE losses were 5.8 days (MR imaging), 6.8 days (combined US and CT), and 8.2 days (CT). This order was sensitive to differences in test performance but was insensitive to variation in radiation-induced cancer deaths. For example, in the same cohort, MR imaging sensitivity had to be 91% at minimum (if specificity were 100%), and MR imaging specificity had to be 62% at minimum (if sensitivity were 100%) to incur the least LE loss. Conversely, LE loss attributable to radiation exposure would need to decrease by 74-fold for combined US and CT, instead of MR imaging, to incur the least LE loss. Conclusion The specific imaging strategy used to diagnose appendicitis minimally affects outcomes. Paradigm shifts to MR imaging owing to concerns over radiation should be considered only if MR imaging test performance is very high. © RSNA, 2014 PMID:24988435

The difficulty of measuring the absorption of scattered sunlight by H2O and CO2 in volcanic plumes: A comment on Pering et al. “A novel and inexpensive method for measuring volcanic plume water fluxes at high temporal resolution,” Remote Sens. 2017, 9, 146

USGS Publications Warehouse

Kern, Christoph

2017-01-01

In their recent study, Pering et al. (2017) presented a novel method for measuring volcanic water vapor fluxes. Their method is based on imaging volcanic gas and aerosol plumes using a camera sensitive to the near-infrared (NIR) absorption of water vapor. The imaging data are empirically calibrated by comparison with in situ water measurements made within the plumes. Though the presented method may give reasonable results over short time scales, the authors fail to recognize the sensitivity of the technique to light scattering on aerosols within the plume. In fact, the signals measured by Pering et al. are not related to the absorption of NIR radiation by water vapor within the plume. Instead, the measured signals are most likely caused by a change in the effective light path of the detected radiation through the atmospheric background water vapor column. Therefore, their method is actually based on establishing an empirical relationship between in-plume scattering efficiency and plume water content. Since this relationship is sensitive to plume aerosol abundance and numerous environmental factors, the method will only yield accurate results if it is calibrated very frequently using other measurement techniques.

Quantitative T1 and T2* carotid atherosclerotic plaque imaging using a three-dimensional multi-echo phase-sensitive inversion recovery sequence: a feasibility study.

PubMed

Fujiwara, Yasuhiro; Maruyama, Hirotoshi; Toyomaru, Kanako; Nishizaka, Yuri; Fukamatsu, Masahiro

2018-06-01

Magnetic resonance imaging (MRI) is widely used to detect carotid atherosclerotic plaques. Although it is important to evaluate vulnerable carotid plaques containing lipids and intra-plaque hemorrhages (IPHs) using T 1 -weighted images, the image contrast changes depending on the imaging settings. Moreover, to distinguish between a thrombus and a hemorrhage, it is useful to evaluate the iron content of the plaque using both T 1 -weighted and T 2 *-weighted images. Therefore, a quantitative evaluation of carotid atherosclerotic plaques using T 1 and T 2 * values may be necessary for the accurate evaluation of plaque components. The purpose of this study was to determine whether the multi-echo phase-sensitive inversion recovery (mPSIR) sequence can improve T 1 contrast while simultaneously providing accurate T 1 and T 2 * values of an IPH. T 1 and T 2 * values measured using mPSIR were compared to values from conventional methods in phantom and in vivo studies. In the phantom study, the T 1 and T 2 * values estimated using mPSIR were linearly correlated with those of conventional methods. In the in vivo study, mPSIR demonstrated higher T 1 contrast between the IPH phantom and sternocleidomastoid muscle than the conventional method. Moreover, the T 1 and T 2 * values of the blood vessel wall and sternocleidomastoid muscle estimated using mPSIR were correlated with values measured by conventional methods and with values reported previously. The mPSIR sequence improved T 1 contrast while simultaneously providing accurate T 1 and T 2 * values of the neck region. Although further study is required to evaluate the clinical utility, mPSIR may improve carotid atherosclerotic plaque detection and provide detailed information about plaque components.

THE ACCURACY OF DIGITAL-VIDEO RETINAL IMAGING TO SCREEN FOR DIABETIC RETINOPATHY: AN ANALYSIS OF TWO DIGITAL-VIDEO RETINAL IMAGING SYSTEMS USING STANDARD STEREOSCOPIC SEVEN-FIELD PHOTOGRAPHY AND DILATED CLINICAL EXAMINATION AS REFERENCE STANDARDS

PubMed Central

Lawrence, Mary Gilbert

2004-01-01

ABSTRACT Purpose To evaluate the accuracy of two digital-video retinal imaging (DVRI) systems to detect diabetic retinopathy. Methods A prospective, masked, technology assessment was conducted for two DVRI systems at a tertiary care Veterans Affairs Medical Center. Group A (n = 151 patients) was imaged with a 640 × 480 resolution system and group B (n = 103 patients) with an 800 × 600 resolution system. Four retinal evaluations were performed on each patient: DVRI with undilated pupils using one imaging field (U-DVRI), DVRI with dilated pupils using three imaging fields (D-DVRI), dilated clinical examination, and Early Treatment Diabetic Retinopathy Study stereoscopic seven-field photography (ETDRS-P). Two analyses of accuracy were conducted, one using ETDRS-P as a “gold standard” (ETDRS-GS) and one using dilated clinical examination as a “gold standard” (C-GS). Results For group A, using the ETDRS-GS, sensitivities of U-DVRI and D-DVRI were 0.66 and 0.66; specificities of U-DVRI and D-DVRI were 0.66 and 0.86. Using the C-GS, sensitivities of U-DVRI and D-DVRI were 0.79 and 0.80; specificities of U-DVRI and D-DVRI were 0.68 and 0.85. For group B, using the ETDRS-GS, sensitivities of U-DVRI and D-DVRI were 0.76 and 0.85; specificities of U-DVRI and D-DVRI were 0.45 and 0.80. Using the C-GS, sensitivities of U-DVRI and D-DVRI were 0.81 and 0.87; specificities of U-DVRI and D-DVRI were 0.45 and 0.69. For both groups, dilation significantly improved specificities. Conclusions The 800 × 600 resolution DVRI system offers an accurate method of detecting diabetic retinopathy, provided there is adequate pupillary dilation and three retinal images are taken. DVRI technology may help facilitate retinal screenings of growing diabetic populations. PMID:15747766

A comparison of earthquake backprojection imaging methods for dense local arrays

NASA Astrophysics Data System (ADS)

Beskardes, G. D.; Hole, J. A.; Wang, K.; Michaelides, M.; Wu, Q.; Chapman, M. C.; Davenport, K. K.; Brown, L. D.; Quiros, D. A.

2018-03-01

Backprojection imaging has recently become a practical method for local earthquake detection and location due to the deployment of densely sampled, continuously recorded, local seismograph arrays. While backprojection sometimes utilizes the full seismic waveform, the waveforms are often pre-processed and simplified to overcome imaging challenges. Real data issues include aliased station spacing, inadequate array aperture, inaccurate velocity model, low signal-to-noise ratio, large noise bursts and varying waveform polarity. We compare the performance of backprojection with four previously used data pre-processing methods: raw waveform, envelope, short-term averaging/long-term averaging and kurtosis. Our primary goal is to detect and locate events smaller than noise by stacking prior to detection to improve the signal-to-noise ratio. The objective is to identify an optimized strategy for automated imaging that is robust in the presence of real-data issues, has the lowest signal-to-noise thresholds for detection and for location, has the best spatial resolution of the source images, preserves magnitude, and considers computational cost. Imaging method performance is assessed using a real aftershock data set recorded by the dense AIDA array following the 2011 Virginia earthquake. Our comparisons show that raw-waveform backprojection provides the best spatial resolution, preserves magnitude and boosts signal to detect events smaller than noise, but is most sensitive to velocity error, polarity error and noise bursts. On the other hand, the other methods avoid polarity error and reduce sensitivity to velocity error, but sacrifice spatial resolution and cannot effectively reduce noise by stacking. Of these, only kurtosis is insensitive to large noise bursts while being as efficient as the raw-waveform method to lower the detection threshold; however, it does not preserve the magnitude information. For automatic detection and location of events in a large data set, we therefore recommend backprojecting kurtosis waveforms, followed by a second pass on the detected events using noise-filtered raw waveforms to achieve the best of all criteria.

Depth-encoded all-fiber swept source polarization sensitive OCT

PubMed Central

Wang, Zhao; Lee, Hsiang-Chieh; Ahsen, Osman Oguz; Lee, ByungKun; Choi, WooJhon; Potsaid, Benjamin; Liu, Jonathan; Jayaraman, Vijaysekhar; Cable, Alex; Kraus, Martin F.; Liang, Kaicheng; Hornegger, Joachim; Fujimoto, James G.

2014-01-01

Polarization sensitive optical coherence tomography (PS-OCT) is a functional extension of conventional OCT and can assess depth-resolved tissue birefringence in addition to intensity. Most existing PS-OCT systems are relatively complex and their clinical translation remains difficult. We present a simple and robust all-fiber PS-OCT system based on swept source technology and polarization depth-encoding. Polarization multiplexing was achieved using a polarization maintaining fiber. Polarization sensitive signals were detected using fiber based polarization beam splitters and polarization controllers were used to remove the polarization ambiguity. A simplified post-processing algorithm was proposed for speckle noise reduction relaxing the demand for phase stability. We demonstrated systems design for both ophthalmic and catheter-based PS-OCT. For ophthalmic imaging, we used an optical clock frequency doubling method to extend the imaging range of a commercially available short cavity light source to improve polarization depth-encoding. For catheter based imaging, we demonstrated 200 kHz PS-OCT imaging using a MEMS-tunable vertical cavity surface emitting laser (VCSEL) and a high speed micromotor imaging catheter. The system was demonstrated in human retina, finger and lip imaging, as well as ex vivo swine esophagus and cardiovascular imaging. The all-fiber PS-OCT is easier to implement and maintain compared to previous PS-OCT systems and can be more easily translated to clinical applications due to its robust design. PMID:25401008

Diagnostic Value of Software-Based Image Fusion of Computed Tomography and F18-FDG PET Scans in Patients with Malignant Lymphoma

PubMed Central

Henninger, B.; Putzer, D.; Kendler, D.; Uprimny, C.; Virgolini, I.; Gunsilius, E.; Bale, R.

2012-01-01

Aim. The purpose of this study was to evaluate the accuracy of 2-deoxy-2-[fluorine-18]fluoro-D-glucose (FDG) positron emission tomography (PET), computed tomography (CT), and software-based image fusion of both modalities in the imaging of non-Hodgkin's lymphoma (NHL) and Hodgkin's disease (HD). Methods. 77 patients with NHL (n = 58) or HD (n = 19) underwent a FDG PET scan, a contrast-enhanced CT, and a subsequent digital image fusion during initial staging or followup. 109 examinations of each modality were evaluated and compared to each other. Conventional staging procedures, other imaging techniques, laboratory screening, and follow-up data constituted the reference standard for comparison with image fusion. Sensitivity and specificity were calculated for CT and PET separately. Results. Sensitivity and specificity for detecting malignant lymphoma were 90% and 76% for CT and 94% and 91% for PET, respectively. A lymph node region-based analysis (comprising 14 defined anatomical regions) revealed a sensitivity of 81% and a specificity of 97% for CT and 96% and 99% for FDG PET, respectively. Only three of 109 image fusion findings needed further evaluation (false positive). Conclusion. Digital fusion of PET and CT improves the accuracy of staging, restaging, and therapy monitoring in patients with malignant lymphoma and may reduce the need for invasive diagnostic procedures. PMID:22654631

Reflective terahertz (THz) imaging: system calibration using hydration phantoms

NASA Astrophysics Data System (ADS)

Bajwa, Neha; Garritano, James; Lee, Yoon Kyung; Tewari, Priyamvada; Sung, Shijun; Maccabi, Ashkan; Nowroozi, Bryan; Babakhanian, Meghedi; Sanghvi, Sajan; Singh, Rahul; Grundfest, Warren; Taylor, Zachary

2013-02-01

Terahertz (THz) hydration sensing continues to gain traction in the medical imaging community due to its unparalleled sensitivity to tissue water content. Rapid and accurate detection of fluid shifts following induction of thermal skin burns as well as remote corneal hydration sensing have been previously demonstrated in vivo using reflective, pulsed THz imaging. The hydration contrast sensing capabilities of this technology were recently confirmed in a parallel 7 Tesla Magnetic Resonance (MR) imaging study, in which burn areas are associated with increases in local mobile water content. Successful clinical translation of THz sensing, however, still requires quantitative assessments of system performance measurements, specifically hydration concentration sensitivity, with tissue substitutes. This research aims to calibrate the sensitivity of a novel, reflective THz system to tissue water content through the use of hydration phantoms for quantitative comparisons of THz hydration imagery.Gelatin phantoms were identified as an appropriate tissue-mimicking model for reflective THz applications, and gel composition, comprising mixtures of water and protein, was varied between 83% to 95% hydration, a physiologically relevant range. A comparison of four series of gelatin phantom studies demonstrated a positive linear relationship between THz reflectivity and water concentration, with statistically significant hydration sensitivities (p < .01) ranging between 0.0209 - 0.038% (reflectivity: %hydration). The THz-phantom interaction is simulated with a three-layer model using the Transfer Matrix Method with agreement in hydration trends. Having demonstrated the ability to accurately and noninvasively measure water content in tissue equivalent targets with high sensitivity, reflective THz imaging is explored as a potential tool for early detection and intervention of corneal pathologies.

Hybrid detection of lung nodules on CT scan images

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lu, Lin; Tan, Yongqiang; Schwartz, Lawrence H.

Purpose: The diversity of lung nodules poses difficulty for the current computer-aided diagnostic (CAD) schemes for lung nodule detection on computed tomography (CT) scan images, especially in large-scale CT screening studies. We proposed a novel CAD scheme based on a hybrid method to address the challenges of detection in diverse lung nodules. Methods: The hybrid method proposed in this paper integrates several existing and widely used algorithms in the field of nodule detection, including morphological operation, dot-enhancement based on Hessian matrix, fuzzy connectedness segmentation, local density maximum algorithm, geodesic distance map, and regression tree classification. All of the adopted algorithmsmore » were organized into tree structures with multi-nodes. Each node in the tree structure aimed to deal with one type of lung nodule. Results: The method has been evaluated on 294 CT scans from the Lung Image Database Consortium (LIDC) dataset. The CT scans were randomly divided into two independent subsets: a training set (196 scans) and a test set (98 scans). In total, the 294 CT scans contained 631 lung nodules, which were annotated by at least two radiologists participating in the LIDC project. The sensitivity and false positive per scan for the training set were 87% and 2.61%. The sensitivity and false positive per scan for the testing set were 85.2% and 3.13%. Conclusions: The proposed hybrid method yielded high performance on the evaluation dataset and exhibits advantages over existing CAD schemes. We believe that the present method would be useful for a wide variety of CT imaging protocols used in both routine diagnosis and screening studies.« less

Development of a high sensitivity pinhole type gamma camera using semiconductors for low dose rate fields

NASA Astrophysics Data System (ADS)

Ueno, Yuichiro; Takahashi, Isao; Ishitsu, Takafumi; Tadokoro, Takahiro; Okada, Koichi; Nagumo, Yasushi; Fujishima, Yasutake; Yoshida, Akira; Umegaki, Kikuo

2018-06-01

We developed a pinhole type gamma camera, using a compact detector module of a pixelated CdTe semiconductor, which has suitable sensitivity and quantitative accuracy for low dose rate fields. In order to improve the sensitivity of the pinhole type semiconductor gamma camera, we adopted three methods: a signal processing method to set the discriminating level lower, a high sensitivity pinhole collimator and a smoothing image filter that improves the efficiency of the source identification. We tested basic performances of the developed gamma camera and carefully examined effects of the three methods. From the sensitivity test, we found that the effective sensitivity was about 21 times higher than that of the gamma camera for high dose rate fields which we had previously developed. We confirmed that the gamma camera had sufficient sensitivity and high quantitative accuracy; for example, a weak hot spot (0.9 μSv/h) around a tree root could be detected within 45 min in a low dose rate field test, and errors of measured dose rates with point sources were less than 7% in a dose rate accuracy test.

Detection of Bone Marrow Edema in Nondisplaced Hip Fractures: Utility of a Virtual Noncalcium Dual-Energy CT Application.

PubMed

Kellock, Trenton T; Nicolaou, Savvas; Kim, Sandra S Y; Al-Busaidi, Sultan; Louis, Luck J; O'Connell, Tim W; Ouellette, Hugue A; McLaughlin, Patrick D

2017-09-01

Purpose To quantify the sensitivity and specificity of dual-energy computed tomographic (CT) virtual noncalcium images in the detection of nondisplaced hip fractures and to assess whether obtaining these images as a complement to bone reconstructions alters sensitivity, specificity, or diagnostic confidence. Materials and Methods The clinical research ethics board approved chart review, and the requirement to obtain informed consent was waived. The authors retrospectively identified 118 patients who presented to a level 1 trauma center emergency department and who underwent dual-energy CT for suspicion of a nondisplaced traumatic hip fracture. Clinical follow-up was the standard of reference. Three radiologists interpreted virtual noncalcium images for traumatic bone marrow edema. Bone reconstructions for the same cases were interpreted alone and then with virtual noncalcium images. Diagnostic confidence was rated on a scale of 1 to 10. McNemar, Fleiss κ, and Wilcoxon signed-rank tests were used for statistical analysis. Results Twenty-two patients had nondisplaced hip fractures and 96 did not have hip fractures. Sensitivity with virtual noncalcium images was 77% and 91% (17 and 20 of 22 patients), and specificity was 92%-99% (89-95 of 96 patients). Sensitivity increased by 4%-5% over that with bone reconstruction images alone for two of the three readers when both bone reconstruction and virtual noncalcium images were used. Specificity remained unchanged (99% and 100%). Diagnostic confidence in the exclusion of fracture was improved with combined bone reconstruction and virtual noncalcium images (median score: 10, 9, and 10 for readers 1, 2, and 3, respectively) compared with bone reconstruction images alone (median score: 9, 8, and 9). Conclusion When used as a supplement to standard bone reconstructions, dual-energy CT virtual noncalcium images increased sensitivity for the detection of nondisplaced traumatic hip fractures and improved diagnostic confidence in the exclusion of these fractures. © RSNA, 2017 Online supplemental material is available for this article. An earlier incorrect version of this article appeared online. This article was corrected on March 17, 2017.

Optimized doppler optical coherence tomography for choroidal capillary vasculature imaging

NASA Astrophysics Data System (ADS)

Liu, Gangjun; Qi, Wenjuan; Yu, Lingfeng; Chen, Zhongping

2011-03-01

In this paper, we analyzed the retinal and choroidal blood vasculature in the posterior segment of the human eye with optimized color Doppler and Doppler variance optical coherence tomography. Depth-resolved structure, color Doppler and Doppler variance images were compared. Blood vessels down to capillary level were able to be obtained with the optimized optical coherence color Doppler and Doppler variance method. For in-vivo imaging of human eyes, bulkmotion induced bulk phase must be identified and removed before using color Doppler method. It was found that the Doppler variance method is not sensitive to bulk motion and the method can be used without removing the bulk phase. A novel, simple and fast segmentation algorithm to indentify retinal pigment epithelium (RPE) was proposed and used to segment the retinal and choroidal layer. The algorithm was based on the detected OCT signal intensity difference between different layers. A spectrometer-based Fourier domain OCT system with a central wavelength of 890 nm and bandwidth of 150nm was used in this study. The 3-dimensional imaging volume contained 120 sequential two dimensional images with 2048 A-lines per image. The total imaging time was 12 seconds and the imaging area was 5x5 mm2.

Radionuclide-fluorescence Reporter Gene Imaging to Track Tumor Progression in Rodent Tumor Models

PubMed Central

Volpe, Alessia; Man, Francis; Lim, Lindsay; Khoshnevisan, Alex; Blower, Julia; Blower, Philip J.; Fruhwirth, Gilbert O.

2018-01-01

Metastasis is responsible for most cancer deaths. Despite extensive research, the mechanistic understanding of the complex processes governing metastasis remains incomplete. In vivo models are paramount for metastasis research, but require refinement. Tracking spontaneous metastasis by non-invasive in vivo imaging is now possible, but remains challenging as it requires long-time observation and high sensitivity. We describe a longitudinal combined radionuclide and fluorescence whole-body in vivo imaging approach for tracking tumor progression and spontaneous metastasis. This reporter gene methodology employs the sodium iodide symporter (NIS) fused to a fluorescent protein (FP). Cancer cells are engineered to stably express NIS-FP followed by selection based on fluorescence-activated cell sorting. Corresponding tumor models are established in mice. NIS-FP expressing cancer cells are tracked non-invasively in vivo at the whole-body level by positron emission tomography (PET) using the NIS radiotracer [18F]BF4-. PET is currently the most sensitive in vivo imaging technology available at this scale and enables reliable and absolute quantification. Current methods either rely on large cohorts of animals that are euthanized for metastasis assessment at varying time points, or rely on barely quantifiable 2D imaging. The advantages of the described method are: (i) highly sensitive non-invasive in vivo 3D PET imaging and quantification, (ii) automated PET tracer production, (iii) a significant reduction in required animal numbers due to repeat imaging options, (iv) the acquisition of paired data from subsequent imaging sessions providing better statistical data, and (v) the intrinsic option for ex vivo confirmation of cancer cells in tissues by fluorescence microscopy or cytometry. In this protocol, we describe all steps required for routine NIS-FP-afforded non-invasive in vivo cancer cell tracking using PET/CT and ex vivo confirmation of in vivo results. This protocol has applications beyond cancer research whenever in vivo localization, expansion and long-time monitoring of a cell population is of interest. PMID:29608157

An authenticated image encryption scheme based on chaotic maps and memory cellular automata

NASA Astrophysics Data System (ADS)

Bakhshandeh, Atieh; Eslami, Ziba

2013-06-01

This paper introduces a new image encryption scheme based on chaotic maps, cellular automata and permutation-diffusion architecture. In the permutation phase, a piecewise linear chaotic map is utilized to confuse the plain-image and in the diffusion phase, we employ the Logistic map as well as a reversible memory cellular automata to obtain an efficient and secure cryptosystem. The proposed method admits advantages such as highly secure diffusion mechanism, computational efficiency and ease of implementation. A novel property of the proposed scheme is its authentication ability which can detect whether the image is tampered during the transmission or not. This is particularly important in applications where image data or part of it contains highly sensitive information. Results of various analyses manifest high security of this new method and its capability for practical image encryption.

Image-guided regularization level set evolution for MR image segmentation and bias field correction.

PubMed

Wang, Lingfeng; Pan, Chunhong

2014-01-01

Magnetic resonance (MR) image segmentation is a crucial step in surgical and treatment planning. In this paper, we propose a level-set-based segmentation method for MR images with intensity inhomogeneous problem. To tackle the initialization sensitivity problem, we propose a new image-guided regularization to restrict the level set function. The maximum a posteriori inference is adopted to unify segmentation and bias field correction within a single framework. Under this framework, both the contour prior and the bias field prior are fully used. As a result, the image intensity inhomogeneity can be well solved. Extensive experiments are provided to evaluate the proposed method, showing significant improvements in both segmentation and bias field correction accuracies as compared with other state-of-the-art approaches. Copyright © 2014 Elsevier Inc. All rights reserved.

Single-cell photoacoustic thermometry

PubMed Central

Gao, Liang; Wang, Lidai; Li, Chiye; Liu, Yan; Ke, Haixin; Zhang, Chi

2013-01-01

Abstract. A novel photoacoustic thermometric method is presented for simultaneously imaging cells and sensing their temperature. With three-seconds-per-frame imaging speed, a temperature resolution of 0.2°C was achieved in a photo-thermal cell heating experiment. Compared to other approaches, the photoacoustic thermometric method has the advantage of not requiring custom-developed temperature-sensitive biosensors. This feature should facilitate the conversion of single-cell thermometry into a routine lab tool and make it accessible to a much broader biological research community. PMID:23377004

Comparison of the sensitivity and specificity of 5 image sets of dual-energy computed tomography for detecting first-pass myocardial perfusion defects compared with positron emission tomography.

PubMed

Li, Wenhuan; Zhu, Xiaolian; Li, Jing; Peng, Cheng; Chen, Nan; Qi, Zhigang; Yang, Qi; Gao, Yan; Zhao, Yang; Sun, Kai; Li, Kuncheng

2014-12-01

The sensitivity and specificity of 5 different image sets of dual-energy computed tomography (DECT) for the detection of first-pass myocardial perfusion defects have not systematically been compared using positron emission tomography (PET) as a reference standard. Forty-nine consecutive patients, with known or strongly suspected of coronary artery disease, were prospectively enrolled in our study. Cardiac DECT was performed at rest state using a second-generation 128-slice dual-source CT. The DECT data were reconstructed to iodine maps, monoenergetic images, 100 kV images, nonlinearly blended images, and linearly blended images by different postprocessing techniques. The myocardial perfusion defects on DECT images were visually assessed by 5 observers, using standard 17-segment model. Diagnostic accuracy of 5 image sets was assessed using nitrogen-13 ammonia PET as the gold standard. Discrimination was quantified using the area under the receiver operating characteristic curve (AUC), and AUCs were compared using the method of DeLong. The DECT and PET examinations were successfully completed in 30 patients and a total of 90 territories and 510 segments were analyzed. Cardiac PET revealed myocardial perfusion defects in 56 territories (62%) and 209 segments (41%). The AUC of iodine maps, monoenergetic images, 100 kV images, nonlinearly blended images, and linearly blended images were 0.986, 0.934, 0.913, 0.881, and 0.871, respectively, on a per-territory basis. These values were 0.922, 0.813, 0.779, 0.763, and 0.728, respectively, on a per-segment basis. DECT iodine maps shows high sensitivity and specificity, and is superior to other DECT image sets for the detection of myocardial perfusion defects in the first-pass myocardial perfusion.

Use of a highly sensitive two-dimensional luminescence imaging system to monitor endogenous bioluminescence in plant leaves

PubMed Central

Flor-Henry, Michel; McCabe, Tulene C; de Bruxelles, Guy L; Roberts, Michael R

2004-01-01

Background All living organisms emit spontaneous low-level bioluminescence, which can be increased in response to stress. Methods for imaging this ultra-weak luminescence have previously been limited by the sensitivity of the detection systems used. Results We developed a novel configuration of a cooled charge-coupled device (CCD) for 2-dimensional imaging of light emission from biological material. In this study, we imaged photon emission from plant leaves. The equipment allowed short integration times for image acquisition, providing high resolution spatial and temporal information on bioluminescence. We were able to carry out time course imaging of both delayed chlorophyll fluorescence from whole leaves, and of low level wound-induced luminescence that we showed to be localised to sites of tissue damage. We found that wound-induced luminescence was chlorophyll-dependent and was enhanced at higher temperatures. Conclusions The data gathered on plant bioluminescence illustrate that the equipment described here represents an improvement in 2-dimensional luminescence imaging technology. Using this system, we identify chlorophyll as the origin of wound-induced luminescence from leaves. PMID:15550176

THz imaging system for in vivo human cornea.

PubMed

Sung, Shijun; Selvin, Skyler; Bajwa, Neha; Chantra, Somporn; Nowroozi, Bryan; Garritano, James; Goell, Jacob; Li, Alex; Deng, Sophie X; Brown, Elliott; Grundfest, Warren S; Taylor, Zachary D

2018-01-01

Terahertz (THz) imaging of corneal tissue water content (CTWC) is a proposed method for early, accurate detection and study of corneal diseases. Despite promising results from ex vivo and in vivo cornea studies, interpretation of the reflectivity data is confounded by the contact between corneal tissue and rigid dielectric window used to flatten the imaging field. This work develops a novel imaging system and image reconstruction methods specifically for nearly spherical targets such as human cornea. A prototype system was constructed using a 650 GHz multiplier source and Schottky diode detector. Resolution and imaging field strength measurement from characterization targets correlate well with those predicted by the quasioptical theory and physical optics analysis. Imaging experiments with corneal phantoms and ex vivo corneas demonstrate the hydration sensitivity of the imaging system and reliable measurement of CTWC. We present successful acquisition of non-contact THz images of in vivo human cornea, and discuss strategies for optimizing the imaging system design for clinical use.

Interference Mitigation Effects on Synthetic Aperture Radar Coherent Data Products

DOE Office of Scientific and Technical Information (OSTI.GOV)

Musgrove, Cameron

2014-05-01

For synthetic aperture radar image products interference can degrade the quality of the images while techniques to mitigate the interference also reduce the image quality. Usually the radar system designer will try to balance the amount of mitigation for the amount of interference to optimize the image quality. This may work well for many situations, but coherent data products derived from the image products are more sensitive than the human eye to distortions caused by interference and mitigation of interference. This dissertation examines the e ect that interference and mitigation of interference has upon coherent data products. An improvement tomore » the standard notch mitigation is introduced, called the equalization notch. Other methods are suggested to mitigation interference while improving the quality of coherent data products over existing methods.« less

Fast and robust standard-deviation-based method for bulk motion compensation in phase-based functional OCT.

PubMed

Wei, Xiang; Camino, Acner; Pi, Shaohua; Cepurna, William; Huang, David; Morrison, John C; Jia, Yali

2018-05-01

Phase-based optical coherence tomography (OCT), such as OCT angiography (OCTA) and Doppler OCT, is sensitive to the confounding phase shift introduced by subject bulk motion. Traditional bulk motion compensation methods are limited by their accuracy and computing cost-effectiveness. In this Letter, to the best of our knowledge, we present a novel bulk motion compensation method for phase-based functional OCT. Bulk motion associated phase shift can be directly derived by solving its equation using a standard deviation of phase-based OCTA and Doppler OCT flow signals. This method was evaluated on rodent retinal images acquired by a prototype visible light OCT and human retinal images acquired by a commercial system. The image quality and computational speed were significantly improved, compared to two conventional phase compensation methods.

A New Method for Automated Identification and Morphometry of Myelinated Fibers Through Light Microscopy Image Analysis.

PubMed

Novas, Romulo Bourget; Fazan, Valeria Paula Sassoli; Felipe, Joaquim Cezar

2016-02-01

Nerve morphometry is known to produce relevant information for the evaluation of several phenomena, such as nerve repair, regeneration, implant, transplant, aging, and different human neuropathies. Manual morphometry is laborious, tedious, time consuming, and subject to many sources of error. Therefore, in this paper, we propose a new method for the automated morphometry of myelinated fibers in cross-section light microscopy images. Images from the recurrent laryngeal nerve of adult rats and the vestibulocochlear nerve of adult guinea pigs were used herein. The proposed pipeline for fiber segmentation is based on the techniques of competitive clustering and concavity analysis. The evaluation of the proposed method for segmentation of images was done by comparing the automatic segmentation with the manual segmentation. To further evaluate the proposed method considering morphometric features extracted from the segmented images, the distributions of these features were tested for statistical significant difference. The method achieved a high overall sensitivity and very low false-positive rates per image. We detect no statistical difference between the distribution of the features extracted from the manual and the pipeline segmentations. The method presented a good overall performance, showing widespread potential in experimental and clinical settings allowing large-scale image analysis and, thus, leading to more reliable results.

Measuring and correcting wobble in large-scale transmission radiography.

PubMed

Rogers, Thomas W; Ollier, James; Morton, Edward J; Griffin, Lewis D

2017-01-01

Large-scale transmission radiography scanners are used to image vehicles and cargo containers. Acquired images are inspected for threats by a human operator or a computer algorithm. To make accurate detections, it is important that image values are precise. However, due to the scale (∼5 m tall) of such systems, they can be mechanically unstable, causing the imaging array to wobble during a scan. This leads to an effective loss of precision in the captured image. We consider the measurement of wobble and amelioration of the consequent loss of image precision. Following our previous work, we use Beam Position Detectors (BPDs) to measure the cross-sectional profile of the X-ray beam, allowing for estimation, and thus correction, of wobble. We propose: (i) a model of image formation with a wobbling detector array; (ii) a method of wobble correction derived from this model; (iii) methods for calibrating sensor sensitivities and relative offsets; (iv) a Random Regression Forest based method for instantaneous estimation of detector wobble; and (v) using these estimates to apply corrections to captured images of difficult scenes. We show that these methods are able to correct for 87% of image error due wobble, and when applied to difficult images, a significant visible improvement in the intensity-windowed image quality is observed. The method improves the precision of wobble affected images, which should help improve detection of threats and the identification of different materials in the image.

Haralick texture features from apparent diffusion coefficient (ADC) MRI images depend on imaging and pre-processing parameters.

PubMed

Brynolfsson, Patrik; Nilsson, David; Torheim, Turid; Asklund, Thomas; Karlsson, Camilla Thellenberg; Trygg, Johan; Nyholm, Tufve; Garpebring, Anders

2017-06-22

In recent years, texture analysis of medical images has become increasingly popular in studies investigating diagnosis, classification and treatment response assessment of cancerous disease. Despite numerous applications in oncology and medical imaging in general, there is no consensus regarding texture analysis workflow, or reporting of parameter settings crucial for replication of results. The aim of this study was to assess how sensitive Haralick texture features of apparent diffusion coefficient (ADC) MR images are to changes in five parameters related to image acquisition and pre-processing: noise, resolution, how the ADC map is constructed, the choice of quantization method, and the number of gray levels in the quantized image. We found that noise, resolution, choice of quantization method and the number of gray levels in the quantized images had a significant influence on most texture features, and that the effect size varied between different features. Different methods for constructing the ADC maps did not have an impact on any texture feature. Based on our results, we recommend using images with similar resolutions and noise levels, using one quantization method, and the same number of gray levels in all quantized images, to make meaningful comparisons of texture feature results between different subjects.

Quantitative method to assess caries via fluorescence imaging from the perspective of autofluorescence spectral analysis

NASA Astrophysics Data System (ADS)

Chen, Q. G.; Zhu, H. H.; Xu, Y.; Lin, B.; Chen, H.

2015-08-01

A quantitative method to discriminate caries lesions for a fluorescence imaging system is proposed in this paper. The autofluorescence spectral investigation of 39 teeth samples classified by the International Caries Detection and Assessment System levels was performed at 405 nm excitation. The major differences in the different caries lesions focused on the relative spectral intensity range of 565-750 nm. The spectral parameter, defined as the ratio of wavebands at 565-750 nm to the whole spectral range, was calculated. The image component ratio R/(G + B) of color components was statistically computed by considering the spectral parameters (e.g. autofluorescence, optical filter, and spectral sensitivity) in our fluorescence color imaging system. Results showed that the spectral parameter and image component ratio presented a linear relation. Therefore, the image component ratio was graded as <0.66, 0.66-1.06, 1.06-1.62, and >1.62 to quantitatively classify sound, early decay, established decay, and severe decay tissues, respectively. Finally, the fluorescence images of caries were experimentally obtained, and the corresponding image component ratio distribution was compared with the classification result. A method to determine the numerical grades of caries using a fluorescence imaging system was proposed. This method can be applied to similar imaging systems.

On the possibility of producing true real-time retinal cross-sectional images using a graphics processing unit enhanced master-slave optical coherence tomography system.

PubMed

Bradu, Adrian; Kapinchev, Konstantin; Barnes, Frederick; Podoleanu, Adrian

2015-07-01

In a previous report, we demonstrated master-slave optical coherence tomography (MS-OCT), an OCT method that does not need resampling of data and can be used to deliver en face images from several depths simultaneously. In a separate report, we have also demonstrated MS-OCT's capability of producing cross-sectional images of a quality similar to those provided by the traditional Fourier domain (FD) OCT technique, but at a much slower rate. Here, we demonstrate that by taking advantage of the parallel processing capabilities offered by the MS-OCT method, cross-sectional OCT images of the human retina can be produced in real time. We analyze the conditions that ensure a true real-time B-scan imaging operation and demonstrate in vivo real-time images from human fovea and the optic nerve, with resolution and sensitivity comparable to those produced using the traditional FD-based method, however, without the need of data resampling.

In-vivo, real-time cross-sectional images of retina using a GPU enhanced master slave optical coherence tomography system

NASA Astrophysics Data System (ADS)

Bradu, Adrian; Kapinchev, Konstantin; Barnes, Frederick; Podoleanu, Adrian

2016-03-01

In our previous reports we demonstrated a novel Fourier domain optical coherence tomography method, Master Slave optical coherence tomography (MS-OCT), that does not require resampling of data and can deliver en-face images from several depths simultaneously. While ideally suited for delivering information from a selected depth, the MS-OCT has been so far inferior to the conventional FFT based OCT in terms of time of producing cross section images. Here, we demonstrate that by taking advantage of the parallel processing capabilities offered by the MS-OCT method, cross-sectional OCT images of the human retina can be produced in real-time by assembling several T-scans from different depths. We analyze the conditions that ensure a real-time B-scan imaging operation, and demonstrate in-vivo real-time images from human fovea and the optic nerve, of comparable resolution and sensitivity to those produced using the traditional Fourier domain based method.

CometQ: An automated tool for the detection and quantification of DNA damage using comet assay image analysis.

PubMed

Ganapathy, Sreelatha; Muraleedharan, Aparna; Sathidevi, Puthumangalathu Savithri; Chand, Parkash; Rajkumar, Ravi Philip

2016-09-01

DNA damage analysis plays an important role in determining the approaches for treatment and prevention of various diseases like cancer, schizophrenia and other heritable diseases. Comet assay is a sensitive and versatile method for DNA damage analysis. The main objective of this work is to implement a fully automated tool for the detection and quantification of DNA damage by analysing comet assay images. The comet assay image analysis consists of four stages: (1) classifier (2) comet segmentation (3) comet partitioning and (4) comet quantification. Main features of the proposed software are the design and development of four comet segmentation methods, and the automatic routing of the input comet assay image to the most suitable one among these methods depending on the type of the image (silver stained or fluorescent stained) as well as the level of DNA damage (heavily damaged or lightly/moderately damaged). A classifier stage, based on support vector machine (SVM) is designed and implemented at the front end, to categorise the input image into one of the above four groups to ensure proper routing. Comet segmentation is followed by comet partitioning which is implemented using a novel technique coined as modified fuzzy clustering. Comet parameters are calculated in the comet quantification stage and are saved in an excel file. Our dataset consists of 600 silver stained images obtained from 40 Schizophrenia patients with different levels of severity, admitted to a tertiary hospital in South India and 56 fluorescent stained images obtained from different internet sources. The performance of "CometQ", the proposed standalone application for automated analysis of comet assay images, is evaluated by a clinical expert and is also compared with that of a most recent and related software-OpenComet. CometQ gave 90.26% positive predictive value (PPV) and 93.34% sensitivity which are much higher than those of OpenComet, especially in the case of silver stained images. The results are validated using confusion matrix and Jaccard index (JI). Comet assay images obtained after DNA damage repair by incubation in the nutrient medium were also analysed, and CometQ showed a significant change in all the comet parameters in most of the cases. Results show that CometQ is an accurate and efficient tool with good sensitivity and PPV for DNA damage analysis using comet assay images. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Fully automated subchondral bone segmentation from knee MR images: Data from the Osteoarthritis Initiative.

PubMed

Gandhamal, Akash; Talbar, Sanjay; Gajre, Suhas; Razak, Ruslan; Hani, Ahmad Fadzil M; Kumar, Dileep

2017-09-01

Knee osteoarthritis (OA) progression can be monitored by measuring changes in the subchondral bone structure such as area and shape from MR images as an imaging biomarker. However, measurements of these minute changes are highly dependent on the accurate segmentation of bone tissue from MR images and it is challenging task due to the complex tissue structure and inadequate image contrast/brightness. In this paper, a fully automated method for segmenting subchondral bone from knee MR images is proposed. Here, the contrast of knee MR images is enhanced using a gray-level S-curve transformation followed by automatic seed point detection using a three-dimensional multi-edge overlapping technique. Successively, bone regions are initially extracted using distance-regularized level-set evolution followed by identification and correction of leakages along the bone boundary regions using a boundary displacement technique. The performance of the developed technique is evaluated against ground truths by measuring sensitivity, specificity, dice similarity coefficient (DSC), average surface distance (AvgD) and root mean square surface distance (RMSD). An average sensitivity (91.14%), specificity (99.12%) and DSC (90.28%) with 95% confidence interval (CI) in the range 89.74-92.54%, 98.93-99.31% and 88.68-91.88% respectively is achieved for the femur bone segmentation in 8 datasets. For tibia bone, average sensitivity (90.69%), specificity (99.65%) and DSC (91.35%) with 95% CI in the range 88.59-92.79%, 99.50-99.80% and 88.68-91.88% respectively is achieved. AvgD and RMSD values for femur are 1.43 ± 0.23 (mm) and 2.10 ± 0.35 (mm) respectively while for tibia, the values are 0.95 ± 0.28 (mm) and 1.30 ± 0.42 (mm) respectively that demonstrates acceptable error between proposed method and ground truths. In conclusion, results obtained in this work demonstrate substantially significant performance with consistency and robustness that led the proposed method to be applicable for large scale and longitudinal knee OA studies in clinical settings. Copyright © 2017 Elsevier Ltd. All rights reserved.

Fluorescence Molecular Tomography: Principles and Potential for Pharmaceutical Research

PubMed Central

Stuker, Florian; Ripoll, Jorge; Rudin, Markus

2011-01-01

Fluorescence microscopic imaging is widely used in biomedical research to study molecular and cellular processes in cell culture or tissue samples. This is motivated by the high inherent sensitivity of fluorescence techniques, the spatial resolution that compares favorably with cellular dimensions, the stability of the fluorescent labels used and the sophisticated labeling strategies that have been developed for selectively labeling target molecules. More recently, two and three-dimensional optical imaging methods have also been applied to monitor biological processes in intact biological organisms such as animals or even humans. These whole body optical imaging approaches have to cope with the fact that biological tissue is a highly scattering and absorbing medium. As a consequence, light propagation in tissue is well described by a diffusion approximation and accurate reconstruction of spatial information is demanding. While in vivo optical imaging is a highly sensitive method, the signal is strongly surface weighted, i.e., the signal detected from the same light source will become weaker the deeper it is embedded in tissue, and strongly depends on the optical properties of the surrounding tissue. Derivation of quantitative information, therefore, requires tomographic techniques such as fluorescence molecular tomography (FMT), which maps the three-dimensional distribution of a fluorescent probe or protein concentration. The combination of FMT with a structural imaging method such as X-ray computed tomography (CT) or Magnetic Resonance Imaging (MRI) will allow mapping molecular information on a high definition anatomical reference and enable the use of prior information on tissue's optical properties to enhance both resolution and sensitivity. Today many of the fluorescent assays originally developed for studies in cellular systems have been successfully translated for experimental studies in animals. The opportunity of monitoring molecular processes non-invasively in the intact organism is highly attractive from a diagnostic point of view but even more so for the drug developer, who can use the techniques for proof-of-mechanism and proof-of-efficacy studies. This review shall elucidate the current status and potential of fluorescence tomography including recent advances in multimodality imaging approaches for preclinical and clinical drug development. PMID:24310495

The x-ray time of flight method for investigation of ghosting in amorphous selenium-based flat panel medical x-ray imagers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rau, A.W.; Bakueva, L.; Rowlands, J.A.

2005-10-15

Amorphous selenium (a-Se) based real-time flat-panel imagers (FPIs) are finding their way into the digital radiology department because they offer the practical advantages of digital x-ray imaging combined with an image quality that equals or outperforms that of conventional systems. The temporal imaging characteristics of FPIs can be affected by ghosting (i.e., radiation-induced changes of sensitivity) when the dose to the detector is high (e.g., portal imaging and mammography) or the images are acquired at a high frame rate (e.g., fluoroscopy). In this paper, the x-ray time-of-flight (TOF) method is introduced as a tool for the investigation of ghosting inmore » a-Se photoconductor layers. The method consists of irradiating layers of a-Se with short x-ray pulses. From the current generated in the a-Se layer, ghosting is quantified and the ghosting parameters (charge carrier generation rate and carrier lifetimes and mobilities) are assessed. The x-ray TOF method is novel in that (1) x-ray sensitivity (S) and ghosting parameters can be measured simultaneously (2) the transport of both holes and electrons can be isolated, and (3) the method is applicable to the practical a-Se layer structure with blocking contacts used in FPIs. The x-ray TOF method was applied to an analysis of ghosting in a-Se photoconductor layers under portal imaging conditions, i.e., 1 mm thick a-Se layers, biased at 5 V/{mu}m, were irradiated using a 6 MV LINAC x-ray beam to a total dose (ghosting dose) of 30 Gy. The initial sensitivity (S{sub 0}) of the a-Se layers was 63{+-}2 nC cm{sup -2} cGy{sup -1}. It was found that S decreases to 30% of S{sub 0} after a ghosting dose of 5 Gy and to 21% after 30 Gy at which point no further change in S occurs. At an x-ray intensity of 22 Gy/s (instantaneous dose rate during a LINAC x-ray pulse), the charge carrier generation rate was 1.25{+-}0.1x10{sup 22} ehp m{sup -3} s{sup -1} and, to a first approximation, independent of the ghosting dose. However, both hole and electron transport showed a strong dependence on the ghosting dose: hole transport decreased by 61%, electron transport by up to {approx}80%. Therefore, degradation of both hole and electron transport due to the recombination of mobile charge carriers with trapped carriers (of opposite polarity) were identified as the main cause of ghosting in this study.« less

Soot Volume Fraction Imaging

NASA Technical Reports Server (NTRS)

Greenberg, Paul S.; Ku, Jerry C.

1994-01-01

A new technique is described for the full-field determination of soot volume fractions via laser extinction measurements. This technique differs from previously reported point-wise methods in that a two-dimensional array (i.e., image) of data is acquired simultaneously. In this fashion, the net data rate is increased, allowing the study of time-dependent phenomena and the investigation of spatial and temporal correlations. A telecentric imaging configuration is employed to provide depth-invariant magnification and to permit the specification of the collection angle for scattered light. To improve the threshold measurement sensitivity, a method is employed to suppress undesirable coherent imaging effects. A discussion of the tomographic inversion process is provided, including the results obtained from numerical simulation. Results obtained with this method from an ethylene diffusion flame are shown to be in close agreement with those previously obtained by sequential point-wise interrogation.

Comparison of Arterial Spin-labeling Perfusion Images at Different Spatial Normalization Methods Based on Voxel-based Statistical Analysis.

PubMed

Tani, Kazuki; Mio, Motohira; Toyofuku, Tatsuo; Kato, Shinichi; Masumoto, Tomoya; Ijichi, Tetsuya; Matsushima, Masatoshi; Morimoto, Shoichi; Hirata, Takumi

2017-01-01

Spatial normalization is a significant image pre-processing operation in statistical parametric mapping (SPM) analysis. The purpose of this study was to clarify the optimal method of spatial normalization for improving diagnostic accuracy in SPM analysis of arterial spin-labeling (ASL) perfusion images. We evaluated the SPM results of five spatial normalization methods obtained by comparing patients with Alzheimer's disease or normal pressure hydrocephalus complicated with dementia and cognitively healthy subjects. We used the following methods: 3DT1-conventional based on spatial normalization using anatomical images; 3DT1-DARTEL based on spatial normalization with DARTEL using anatomical images; 3DT1-conventional template and 3DT1-DARTEL template, created by averaging cognitively healthy subjects spatially normalized using the above methods; and ASL-DARTEL template created by averaging cognitively healthy subjects spatially normalized with DARTEL using ASL images only. Our results showed that ASL-DARTEL template was small compared with the other two templates. Our SPM results obtained with ASL-DARTEL template method were inaccurate. Also, there were no significant differences between 3DT1-conventional and 3DT1-DARTEL template methods. In contrast, the 3DT1-DARTEL method showed higher detection sensitivity, and precise anatomical location. Our SPM results suggest that we should perform spatial normalization with DARTEL using anatomical images.

Using false colors to protect visual privacy of sensitive content

NASA Astrophysics Data System (ADS)

Ćiftçi, Serdar; Korshunov, Pavel; Akyüz, Ahmet O.; Ebrahimi, Touradj

2015-03-01

Many privacy protection tools have been proposed for preserving privacy. Tools for protection of visual privacy available today lack either all or some of the important properties that are expected from such tools. Therefore, in this paper, we propose a simple yet effective method for privacy protection based on false color visualization, which maps color palette of an image into a different color palette, possibly after a compressive point transformation of the original pixel data, distorting the details of the original image. This method does not require any prior face detection or other sensitive regions detection and, hence, unlike typical privacy protection methods, it is less sensitive to inaccurate computer vision algorithms. It is also secure as the look-up tables can be encrypted, reversible as table look-ups can be inverted, flexible as it is independent of format or encoding, adjustable as the final result can be computed by interpolating the false color image with the original using different degrees of interpolation, less distracting as it does not create visually unpleasant artifacts, and selective as it preserves better semantic structure of the input. Four different color scales and four different compression functions, one which the proposed method relies, are evaluated via objective (three face recognition algorithms) and subjective (50 human subjects in an online-based study) assessments using faces from FERET public dataset. The evaluations demonstrate that DEF and RBS color scales lead to the strongest privacy protection, while compression functions add little to the strength of privacy protection. Statistical analysis also shows that recognition algorithms and human subjects perceive the proposed protection similarly

Computerized detection of breast cancer on automated breast ultrasound imaging of women with dense breasts

DOE Office of Scientific and Technical Information (OSTI.GOV)

Drukker, Karen, E-mail: kdrukker@uchicago.edu; Sennett, Charlene A.; Giger, Maryellen L.

2014-01-15

Purpose: Develop a computer-aided detection method and investigate its feasibility for detection of breast cancer in automated 3D ultrasound images of women with dense breasts. Methods: The HIPAA compliant study involved a dataset of volumetric ultrasound image data, “views,” acquired with an automated U-Systems Somo•V{sup ®} ABUS system for 185 asymptomatic women with dense breasts (BI-RADS Composition/Density 3 or 4). For each patient, three whole-breast views (3D image volumes) per breast were acquired. A total of 52 patients had breast cancer (61 cancers), diagnosed through any follow-up at most 365 days after the original screening mammogram. Thirty-one of these patientsmore » (32 cancers) had a screening-mammogram with a clinically assigned BI-RADS Assessment Category 1 or 2, i.e., were mammographically negative. All software used for analysis was developed in-house and involved 3 steps: (1) detection of initial tumor candidates, (2) characterization of candidates, and (3) elimination of false-positive candidates. Performance was assessed by calculating the cancer detection sensitivity as a function of the number of “marks” (detections) per view. Results: At a single mark per view, i.e., six marks per patient, the median detection sensitivity by cancer was 50.0% (16/32) ± 6% for patients with a screening mammogram-assigned BI-RADS category 1 or 2—similar to radiologists’ performance sensitivity (49.9%) for this dataset from a prior reader study—and 45.9% (28/61) ± 4% for all patients. Conclusions: Promising detection sensitivity was obtained for the computer on a 3D ultrasound dataset of women with dense breasts at a rate of false-positive detections that may be acceptable for clinical implementation.« less

Automatic Segmentation of Invasive Breast Carcinomas from DCE-MRI using Time Series Analysis

PubMed Central

Jayender, Jagadaeesan; Chikarmane, Sona; Jolesz, Ferenc A.; Gombos, Eva

2013-01-01

Purpose Quantitative segmentation methods based on black-box modeling and pharmacokinetic modeling are highly dependent on imaging pulse sequence, timing of bolus injection, arterial input function, imaging noise and fitting algorithms. To accurately segment invasive ductal carcinomas (IDCs) from dynamic contrast enhanced MRI (DCE-MRI) using time series analysis based on linear dynamic system (LDS) modeling. Methods We modeled the underlying dynamics of the tumor by a LDS and use the system parameters to segment the carcinoma on the DCE-MRI. Twenty-four patients with biopsy-proven IDCs were analyzed. The lesions segmented by the algorithm were compared with an expert radiologist’s segmentation and the output of a commercial software, CADstream. The results are quantified in terms of the accuracy and sensitivity of detecting the lesion and the amount of overlap, measured in terms of the Dice similarity coefficient (DSC). Results The segmentation algorithm detected the tumor with 90% accuracy and 100% sensitivity when compared to the radiologist’s segmentation and 82.1% accuracy and 100% sensitivity when compared to the CADstream output. The overlap of the algorithm output with the radiologist’s segmentation and CADstream output, computed in terms of the DSC was 0.77 and 0.72 respectively. The algorithm also shows robust stability to imaging noise. Simulated imaging noise with zero mean and standard deviation equal to 25% of the base signal intensity was added to the DCE-MRI series. The amount of overlap between the tumor maps generated by the LDS-based algorithm from the noisy and original DCE-MRI was DSC=0.95. Conclusion The time-series analysis based segmentation algorithm provides high accuracy and sensitivity in delineating the regions of enhanced perfusion corresponding to tumor from DCE-MRI. PMID:24115175

Comparison of magnetic resonance imaging (MRI) and contrast-enhanced ultrasound (CEUS) in the evaluation of unclear solid renal lesions.

PubMed

Rübenthaler, J; Paprottka, K; Marcon, J; Hameister, E; Hoffmann, K; Joiko, N; Reiser, M; Clevert, D A

2016-01-01

To compare the sensitivity and specificity of contrast-enhanced ultrasound (CEUS) and magnetic resonance imaging (MRI) in the evaluation of unclear renal lesions to the histopathological outcome. A total of 36 patients with a single unclear solid renal lesion with initial imaging studies between 2005 and 2015 were included. CEUS and MRI were used for determining malignancy or benignancy and initial findings were correlated with the histopathological outcome. Out of the 36 renal masses a total of 28 lesions were malignant (77.8%) and 8 were found to be benign (22.2%). Diagnostic accuracy was testes by using the histopathological diagnosis as the gold standard. CEUS showed a sensitivity of 96.4%, a specificity of 100.0%, a positive predictive value (PPV) of 100.0% and a negative predictive value (NPV) of 88,9%. MRI showed a sensitivity of 96.4%, a specificity of 75.0%, a PPV of 93.1% and a NPV of 85.7%. Out of the 28 malignant lesions a total of 18 clear cell renal carcinomas, 6 papillary renal cell carcinomas and 4 other malignant lesions, e.g. metastases, were diagnosed. Out of the 8 benign lesions a total 3 angiomyolipomas, 2 oncocytomas, 1 benign renal cyst and 2 other benign lesions, e.g. renal adenomas were diagnosed. Using CEUS, 1 lesion was falsely identified as benign. Using MRI, 2 lesions were falsely identified as benign and 1 lesion was falsely identified as malignant. CEUS is an useful method which can be additionally used to clinically differentiate between malignant and benign renal lesions. CEUS shows a comparable sensitivity, specificity, PPV and NPV to MRI. In daily clinical routine, patients with contraindications for other imaging modalities can particularly benefit using this method.

Role of serial multiparametric magnetic resonance imaging in prostate cancer active surveillance

PubMed Central

Vos, Larissa J; Janoski, Michele; Wachowicz, Keith; Yahya, Atiyah; Boychak, Oleksandr; Amanie, John; Pervez, Nadeem; Parliament, Matthew B; Pituskin, Edith; Fallone, B Gino; Usmani, Nawaid

2016-01-01

AIM: To examine whether addition of 3T multiparametric magnetic resonance imaging (mpMRI) to an active surveillance protocol could detect aggressive or progressive prostate cancer. METHODS: Twenty-three patients with low risk disease were enrolled on this active surveillance study, all of which had Gleason score 6 or less disease. All patients had clinical assessments, including digital rectal examination and prostate specific antigen (PSA) testing, every 6 mo with annual 3T mpMRI scans with gadolinium contrast and minimum sextant prostate biopsies. The MRI images were anonymized of patient identifiers and clinical information and each scan underwent radiological review without the other results known. Descriptive statistics for demographics and follow-up as well as the sensitivity and specificity of mpMRI to identify prostate cancer and progressive disease were calculated. RESULTS: During follow-up (median 24.8 mo) 11 of 23 patients with low-risk prostate cancer had disease progression and were taken off study to receive definitive treatment. Disease progression was identified through upstaging of Gleason score on subsequent biopsies for all 11 patients with only 2 patients also having a PSA doubling time of less than 2 years. All 23 patients had biopsy confirmed prostate cancer but only 10 had a positive index of suspicion on mpMRI scans at baseline (43.5% sensitivity). Aggressive disease prediction from baseline mpMRI scans had satisfactory specificity (81.8%) but low sensitivity (58.3%). Twenty-two patients had serial mpMRI scans and evidence of disease progression was seen for 3 patients all of whom had upstaging of Gleason score on biopsy (30% specificity and 100% sensitivity). CONCLUSION: Addition of mpMRI imaging in active surveillance decision making may help in identifying aggressive disease amongst men with indolent prostate cancer earlier than traditional methods. PMID:27158428

Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs.

PubMed

Gulshan, Varun; Peng, Lily; Coram, Marc; Stumpe, Martin C; Wu, Derek; Narayanaswamy, Arunachalam; Venugopalan, Subhashini; Widner, Kasumi; Madams, Tom; Cuadros, Jorge; Kim, Ramasamy; Raman, Rajiv; Nelson, Philip C; Mega, Jessica L; Webster, Dale R

2016-12-13

Deep learning is a family of computational methods that allow an algorithm to program itself by learning from a large set of examples that demonstrate the desired behavior, removing the need to specify rules explicitly. Application of these methods to medical imaging requires further assessment and validation. To apply deep learning to create an algorithm for automated detection of diabetic retinopathy and diabetic macular edema in retinal fundus photographs. A specific type of neural network optimized for image classification called a deep convolutional neural network was trained using a retrospective development data set of 128 175 retinal images, which were graded 3 to 7 times for diabetic retinopathy, diabetic macular edema, and image gradability by a panel of 54 US licensed ophthalmologists and ophthalmology senior residents between May and December 2015. The resultant algorithm was validated in January and February 2016 using 2 separate data sets, both graded by at least 7 US board-certified ophthalmologists with high intragrader consistency. Deep learning-trained algorithm. The sensitivity and specificity of the algorithm for detecting referable diabetic retinopathy (RDR), defined as moderate and worse diabetic retinopathy, referable diabetic macular edema, or both, were generated based on the reference standard of the majority decision of the ophthalmologist panel. The algorithm was evaluated at 2 operating points selected from the development set, one selected for high specificity and another for high sensitivity. The EyePACS-1 data set consisted of 9963 images from 4997 patients (mean age, 54.4 years; 62.2% women; prevalence of RDR, 683/8878 fully gradable images [7.8%]); the Messidor-2 data set had 1748 images from 874 patients (mean age, 57.6 years; 42.6% women; prevalence of RDR, 254/1745 fully gradable images [14.6%]). For detecting RDR, the algorithm had an area under the receiver operating curve of 0.991 (95% CI, 0.988-0.993) for EyePACS-1 and 0.990 (95% CI, 0.986-0.995) for Messidor-2. Using the first operating cut point with high specificity, for EyePACS-1, the sensitivity was 90.3% (95% CI, 87.5%-92.7%) and the specificity was 98.1% (95% CI, 97.8%-98.5%). For Messidor-2, the sensitivity was 87.0% (95% CI, 81.1%-91.0%) and the specificity was 98.5% (95% CI, 97.7%-99.1%). Using a second operating point with high sensitivity in the development set, for EyePACS-1 the sensitivity was 97.5% and specificity was 93.4% and for Messidor-2 the sensitivity was 96.1% and specificity was 93.9%. In this evaluation of retinal fundus photographs from adults with diabetes, an algorithm based on deep machine learning had high sensitivity and specificity for detecting referable diabetic retinopathy. Further research is necessary to determine the feasibility of applying this algorithm in the clinical setting and to determine whether use of the algorithm could lead to improved care and outcomes compared with current ophthalmologic assessment.

Microscopic lymph node tumor burden quantified by macroscopic dual-tracer molecular imaging

PubMed Central

Tichauer, Kenneth M.; Samkoe, Kimberley S.; Gunn, Jason R.; Kanick, Stephen C.; Hoopes, P. Jack; Barth, Richard J.; Kaufman, Peter A.; Hasan, Tayyaba; Pogue, Brian W.

2014-01-01

Lymph node biopsy (LNB) is employed in many cancer surgeries to identify metastatic disease and stage the cancer, yet morbidity and diagnostic delays associated with LNB could be avoided if non-invasive imaging of nodal involvement was reliable. Molecular imaging has potential in this regard; however, variable delivery and nonspecific uptake of imaging tracers has made conventional approaches ineffective clinically. A method of correcting for non-specific uptake with injection of a second untargeted tracer is presented, allowing tumor burden in lymph nodes to be quantified. The approach was confirmed in an athymic mouse model of metastatic human breast cancer targeting epidermal growth factor receptor, a cell surface receptor overexpressed by many cancers. A significant correlation was observed between in vivo (dual-tracer) and ex vivo measures of tumor burden (r = 0.97, p < 0.01), with an ultimate sensitivity of approximately 200 cells (potentially more sensitive than conventional LNB). PMID:25344739

A Study on the Application of Normalized Point Source Sensitivity in Wide Field Optical Spectrometer of the Thirty Meter Telescope

NASA Astrophysics Data System (ADS)

Chen, Li-si; Hu, Zhong-wen

2017-10-01

The image evaluation of an optical system is the core of optical design. Based on the analysis and comparison of the PSSN (Normalized Point Source Sensitivity) proposed in the image evaluation of the TMT (Thirty Meter Telescope) and the common image evaluation methods, the application of PSSN in the TMT WFOS (Wide Field Optical Spectrometer) is studied. It includes an approximate simulation of the atmospheric seeing, the effect of the displacement of M3 in the TMT on the PSSN of the system, the effect of the displacement of collimating mirror in the WFOS on the PSSN of the system, the relations between the PSSN and the zenith angle under different conditions of atmospheric turbulence, and the relation between the PSSN and the wavefront aberration. The results show that the PSSN is effective for the image evaluation of the TMT under a limited atmospheric seeing.

High resolution Cerenkov light imaging of induced positron distribution in proton therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yamamoto, Seiichi, E-mail: s-yama@met.nagoya-u.ac.jp; Fujii, Kento; Morishita, Yuki

2014-11-01

Purpose: In proton therapy, imaging of the positron distribution produced by fragmentation during or soon after proton irradiation is a useful method to monitor the proton range. Although positron emission tomography (PET) is typically used for this imaging, its spatial resolution is limited. Cerenkov light imaging is a new molecular imaging technology that detects the visible photons that are produced from high-speed electrons using a high sensitivity optical camera. Because its inherent spatial resolution is much higher than PET, the authors can measure more precise information of the proton-induced positron distribution with Cerenkov light imaging technology. For this purpose, theymore » conducted Cerenkov light imaging of induced positron distribution in proton therapy. Methods: First, the authors evaluated the spatial resolution of our Cerenkov light imaging system with a {sup 22}Na point source for the actual imaging setup. Then the transparent acrylic phantoms (100 × 100 × 100 mm{sup 3}) were irradiated with two different proton energies using a spot scanning proton therapy system. Cerenkov light imaging of each phantom was conducted using a high sensitivity electron multiplied charge coupled device (EM-CCD) camera. Results: The Cerenkov light’s spatial resolution for the setup was 0.76 ± 0.6 mm FWHM. They obtained high resolution Cerenkov light images of the positron distributions in the phantoms for two different proton energies and made fused images of the reference images and the Cerenkov light images. The depths of the positron distribution in the phantoms from the Cerenkov light images were almost identical to the simulation results. The decay curves derived from the region-of-interests (ROIs) set on the Cerenkov light images revealed that Cerenkov light images can be used for estimating the half-life of the radionuclide components of positrons. Conclusions: High resolution Cerenkov light imaging of proton-induced positron distribution was possible. The authors conclude that Cerenkov light imaging of proton-induced positron is promising for proton therapy.« less

TH-AB-209-07: High Resolution X-Ray-Induced Acoustic Computed Tomography

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xiang, L; Tang, S; Ahmad, M

Purpose: X-ray radiographic absorption imaging is an invaluable tool in medical diagnostics, biology and materials science. However, the use of conventional CT is limited by two factors: the detection sensitivity to weak absorption material and the radiation dose from CT scanning. The purpose of this study is to explore X-ray induced acoustic computed tomography (XACT), a new imaging modality, which combines X-ray absorption contrast and high ultrasonic resolution to address these challenges. Methods: First, theoretical models was built to analyze the XACT sensitivity to X-ray absorption and calculate the minimal radiation dose in XACT imaging. Then, an XACT system comprisedmore » of an ultrashort X-ray pulse, a low noise ultrasound detector and a signal acquisition system was built to evaluate the X-ray induced acoustic signal generation. A piece of chicken bone and a phantom with two golden fiducial markers were exposed to 270 kVp X-ray source with 60 ns exposure time, and the X-ray induced acoustic signal was received by a 2.25MHz ultrasound transducer in 200 positions. XACT images were reconstructed by a filtered back-projection algorithm. Results: The theoretical analysis shows that X-ray induced acoustic signals have 100% relative sensitivity to X-ray absorption, but not to X-ray scattering. Applying this innovative technology to breast imaging, we can reduce radiation dose by a factor of 50 compared with newly FDA approved breast CT. The reconstructed images of chicken bone and golden fiducial marker phantom reveal that the spatial resolution of the built XACT system is 350µm. Conclusion: In XACT, the imaging sensitivity to X-ray absorption is improved and the imaging dose is dramatically reduced by using ultrashort pulsed X-ray. Taking advantage of the high ultrasonic resolution, we can also perform 3D imaging with a single X-ray pulse. This new modality has the potential to revolutionize x-ray imaging applications in medicine and biology.« less

Infrared Ship Target Segmentation Based on Spatial Information Improved FCM.

PubMed

Bai, Xiangzhi; Chen, Zhiguo; Zhang, Yu; Liu, Zhaoying; Lu, Yi

2016-12-01

Segmentation of infrared (IR) ship images is always a challenging task, because of the intensity inhomogeneity and noise. The fuzzy C-means (FCM) clustering is a classical method widely used in image segmentation. However, it has some shortcomings, like not considering the spatial information or being sensitive to noise. In this paper, an improved FCM method based on the spatial information is proposed for IR ship target segmentation. The improvements include two parts: 1) adding the nonlocal spatial information based on the ship target and 2) using the spatial shape information of the contour of the ship target to refine the local spatial constraint by Markov random field. In addition, the results of K -means are used to initialize the improved FCM method. Experimental results show that the improved method is effective and performs better than the existing methods, including the existing FCM methods, for segmentation of the IR ship images.

A new instrument of VUV laser desorption/ionization mass spectrometry imaging with micrometer spatial resolution and low level of molecular fragmentation.

PubMed

Wang, Jia; Liu, Feng; Mo, Yuxiang; Wang, Zhaoying; Zhang, Sichun; Zhang, Xinrong

2017-11-01

Mass spectrometry imaging (MSI) has important applications in material research, biology, and medicine. The MSI method based on UV laser desorption/ionization (UVLDI) can obtain images of intact samples, but has a high level of molecular fragmentation. In this work, we report a new MSI instrument that uses a VUV laser (125.3 nm) as a desorption/ionization source to exploit its advantages of high single photon energy and small focus size. The new instrument was tested by the mass spectra of Nile red and FGB (Fibrinogen beta chain) samples and mass spectrometric images of a fly brain section. For the tested samples, the VUVDI method offers lower levels of molecular fragmentations and higher sensitivities than those of the UVLDI method and second ion mass spectrometry imaging method using a Bi 3 + beam. The ablation crater produced by the focused VUV laser on a quartz plate has an area of 10 μm 2 . The VUV laser is prepared based on the four-wave mixing method using three collimated laser beams and a heated Hg cell.

A new instrument of VUV laser desorption/ionization mass spectrometry imaging with micrometer spatial resolution and low level of molecular fragmentation

NASA Astrophysics Data System (ADS)

Wang, Jia; Liu, Feng; Mo, Yuxiang; Wang, Zhaoying; Zhang, Sichun; Zhang, Xinrong

2017-11-01

Mass spectrometry imaging (MSI) has important applications in material research, biology, and medicine. The MSI method based on UV laser desorption/ionization (UVLDI) can obtain images of intact samples, but has a high level of molecular fragmentation. In this work, we report a new MSI instrument that uses a VUV laser (125.3 nm) as a desorption/ionization source to exploit its advantages of high single photon energy and small focus size. The new instrument was tested by the mass spectra of Nile red and FGB (Fibrinogen beta chain) samples and mass spectrometric images of a fly brain section. For the tested samples, the VUVDI method offers lower levels of molecular fragmentations and higher sensitivities than those of the UVLDI method and second ion mass spectrometry imaging method using a Bi3+ beam. The ablation crater produced by the focused VUV laser on a quartz plate has an area of 10 μm2. The VUV laser is prepared based on the four-wave mixing method using three collimated laser beams and a heated Hg cell.

SU-F-J-59: Assessment of Dose Response Distribution in Individual Human Tumor

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yan, D; Chen, S; Krauss, D

Purpose: To fulfill precision radiotherapy via adaptive dose painting by number, voxel-by-voxel dose response or radio-sensitivity in individual human tumor needs to be determined in early treatment to guide treatment adaptation. In this study, multiple FDG PET images obtained pre- and weekly during the treatment course were utilized to determine the distribution/spectrum of dose response parameters in individual human tumors. Methods: FDG PET/CT images of 18 HN cancer patients were used in the study. Spatial parametric image of tumor metabolic ratio (dSUV) was created following voxel by voxel deformable image registration. Each voxel value in dSUV was a function ofmore » pre-treatment baseline SUV and treatment delivered dose, and used as a surrogate of tumor survival fraction (SF). Regression fitting with break points was performed using the LQ-model with tumor proliferation for the control and failure group of tumors separately. The distribution and spectrum of radiation sensitivity and growth in individual tumors were determined and evaluated. Results: Spectrum of tumor dose-sensitivity and proliferation in the controlled group was broad with α in tumor survival LQ-model from 0.17 to 0.8. It was proportional to the baseline SUV. Tlag was about 21∼25 days, and Tpot about 0.56∼1.67 days respectively. Commonly tumor voxels with high radio-sensitivity or larger α had small Tlag and Tpot. For the failure group, the radio-sensitivity α was low within 0.05 to 0.3, but did not show clear Tlag. In addition, tumor voxel radio-sensitivity could be estimated during the early treatment weeks. Conclusion: Dose response distribution with respect to radio-sensitivity and growth in individual human tumor can be determined using FDG PET imaging based tumor metabolic ratio measured in early treatment course. The discover is critical and provides a potential quantitative objective to implement tumor specific precision radiotherapy via adaptive dose painting by number.« less

Assessment of cardiac fibrosis: a morphometric method comparison for collagen quantification.

PubMed

Schipke, Julia; Brandenberger, Christina; Rajces, Alexandra; Manninger, Martin; Alogna, Alessio; Post, Heiner; Mühlfeld, Christian

2017-04-01

Fibrotic remodeling of the heart is a frequent condition linked to various diseases and cardiac dysfunction. Collagen quantification is an important objective in cardiac fibrosis research; however, a variety of different histological methods are currently used that may differ in accuracy. Here, frequently applied collagen quantification techniques were compared. A porcine model of early stage heart failure with preserved ejection fraction was used as an example. Semiautomated threshold analyses were imprecise, mainly due to inclusion of noncollagen structures or failure to detect certain collagen deposits. In contrast, collagen assessment by automated image analysis and light microscopy (LM)-stereology was more sensitive. Depending on the quantification method, the amount of estimated collagen varied and influenced intergroup comparisons. PicroSirius Red, Masson's trichrome, and Azan staining protocols yielded similar results, whereas the measured collagen area increased with increasing section thickness. Whereas none of the LM-based methods showed significant differences between the groups, electron microscopy (EM)-stereology revealed a significant collagen increase between cardiomyocytes in the experimental group, but not at other localizations. In conclusion, in contrast to the staining protocol, section thickness and the quantification method being used directly influence the estimated collagen content and thus, possibly, intergroup comparisons. EM in combination with stereology is a precise and sensitive method for collagen quantification if certain prerequisites are considered. For subtle fibrotic alterations, consideration of collagen localization may be necessary. Among LM methods, LM-stereology and automated image analysis are appropriate to quantify fibrotic changes, the latter depending on careful control of algorithm and comparable section staining. NEW & NOTEWORTHY Direct comparison of frequently applied histological fibrosis assessment techniques revealed a distinct relation of measured collagen and utilized quantification method as well as section thickness. Besides electron microscopy-stereology, which was precise and sensitive, light microscopy-stereology and automated image analysis proved to be appropriate for collagen quantification. Moreover, consideration of collagen localization might be important in revealing minor fibrotic changes. Copyright © 2017 the American Physiological Society.

Probabilistic brain tissue segmentation in neonatal magnetic resonance imaging.

PubMed

Anbeek, Petronella; Vincken, Koen L; Groenendaal, Floris; Koeman, Annemieke; van Osch, Matthias J P; van der Grond, Jeroen

2008-02-01

A fully automated method has been developed for segmentation of four different structures in the neonatal brain: white matter (WM), central gray matter (CEGM), cortical gray matter (COGM), and cerebrospinal fluid (CSF). The segmentation algorithm is based on information from T2-weighted (T2-w) and inversion recovery (IR) scans. The method uses a K nearest neighbor (KNN) classification technique with features derived from spatial information and voxel intensities. Probabilistic segmentations of each tissue type were generated. By applying thresholds on these probability maps, binary segmentations were obtained. These final segmentations were evaluated by comparison with a gold standard. The sensitivity, specificity, and Dice similarity index (SI) were calculated for quantitative validation of the results. High sensitivity and specificity with respect to the gold standard were reached: sensitivity >0.82 and specificity >0.9 for all tissue types. Tissue volumes were calculated from the binary and probabilistic segmentations. The probabilistic segmentation volumes of all tissue types accurately estimated the gold standard volumes. The KNN approach offers valuable ways for neonatal brain segmentation. The probabilistic outcomes provide a useful tool for accurate volume measurements. The described method is based on routine diagnostic magnetic resonance imaging (MRI) and is suitable for large population studies.

Microscale reconstruction of biogeochemical substrates using multimode X-ray tomography and scanning electron microscopy

NASA Astrophysics Data System (ADS)

Miller, M.; Miller, E.; Liu, J.; Lund, R. M.; McKinley, J. P.

2012-12-01

X-ray computed tomography (CT), scanning electron microscopy (SEM), electron microprobe analysis (EMP), and computational image analysis are mature technologies used in many disciplines. Cross-discipline combination of these imaging and image-analysis technologies is the focus of this research, which uses laboratory and light-source resources in an iterative approach. The objective is to produce images across length scales, taking advantage of instrumentation that is optimized for each scale, and to unify them into a single compositional reconstruction. Initially, CT images will be collected using both x-ray absorption and differential phase contrast modes. The imaged sample will then be physically sectioned and the exposed surfaces imaged and characterized via SEM/EMP. The voxel slice corresponding to the physical sample surface will be isolated computationally, and the volumetric data will be combined with two-dimensional SEM images along CT image planes. This registration step will take advantage of the similarity between the X-ray absorption (CT) and backscattered electron (SEM) coefficients (both proportional to average atomic number in the interrogated volume) as well as the images' mutual information. Elemental and solid-phase distributions on the exposed surfaces, co-registered with SEM images, will be mapped using EMP. The solid-phase distribution will be propagated into three-dimensional space using computational methods relying on the estimation of compositional distributions derived from the CT data. If necessary, solid-phase and pore-space boundaries will be resolved using X-ray differential phase contrast tomography, x-ray fluorescence tomography, and absorption-edge microtomography at a light-source facility. Computational methods will be developed to register and model images collected over varying scales and data types. Image resolution, physically and dynamically, is qualitatively different for the electron microscopy and CT methodologies. Routine CT images are resolved at 10-20 μm, while SEM images are resolved at 10-20 nm; grayscale values vary according to collection time and instrument sensitivity; and compositional sensitivities via EMP vary in interrogation volume and scale. We have so far successfully registered SEM imagery within a multimode tomographic volume and have used standard methods to isolate pore space within the volume. We are developing a three-dimensional solid-phase identification and registration method that is constrained by bulk-sample X-ray diffraction Rietveld refinements. The results of this project will prove useful in fields that require the fine-scale definition of solid-phase distributions and relationships, and could replace more inefficient methods for making these estimations.

Interleaved diffusion-weighted EPI improved by adaptive partial-Fourier and multi-band multiplexed sensitivity-encoding reconstruction

PubMed Central

Chang, Hing-Chiu; Guhaniyogi, Shayan; Chen, Nan-kuei

2014-01-01

Purpose We report a series of techniques to reliably eliminate artifacts in interleaved echo-planar imaging (EPI) based diffusion weighted imaging (DWI). Methods First, we integrate the previously reported multiplexed sensitivity encoding (MUSE) algorithm with a new adaptive Homodyne partial-Fourier reconstruction algorithm, so that images reconstructed from interleaved partial-Fourier DWI data are free from artifacts even in the presence of either a) motion-induced k-space energy peak displacement, or b) susceptibility field gradient induced fast phase changes. Second, we generalize the previously reported single-band MUSE framework to multi-band MUSE, so that both through-plane and in-plane aliasing artifacts in multi-band multi-shot interleaved DWI data can be effectively eliminated. Results The new adaptive Homodyne-MUSE reconstruction algorithm reliably produces high-quality and high-resolution DWI, eliminating residual artifacts in images reconstructed with previously reported methods. Furthermore, the generalized MUSE algorithm is compatible with multi-band and high-throughput DWI. Conclusion The integration of the multi-band and adaptive Homodyne-MUSE algorithms significantly improves the spatial-resolution, image quality, and scan throughput of interleaved DWI. We expect that the reported reconstruction framework will play an important role in enabling high-resolution DWI for both neuroscience research and clinical uses. PMID:24925000

G-Channel Restoration for RWB CFA with Double-Exposed W Channel

PubMed Central

Park, Chulhee; Song, Ki Sun; Kang, Moon Gi

2017-01-01

In this paper, we propose a green (G)-channel restoration for a red–white–blue (RWB) color filter array (CFA) image sensor using the dual sampling technique. By using white (W) pixels instead of G pixels, the RWB CFA provides high-sensitivity imaging and an improved signal-to-noise ratio compared to the Bayer CFA. However, owing to this high sensitivity, the W pixel values become rapidly over-saturated before the red–blue (RB) pixel values reach the appropriate levels. Because the missing G color information included in the W channel cannot be restored with a saturated W, multiple captures with dual sampling are necessary to solve this early W-pixel saturation problem. Each W pixel has a different exposure time when compared to those of the R and B pixels, because the W pixels are double-exposed. Therefore, a RWB-to-RGB color conversion method is required in order to restore the G color information, using a double-exposed W channel. The proposed G-channel restoration algorithm restores G color information from the W channel by considering the energy difference caused by the different exposure times. Using the proposed method, the RGB full-color image can be obtained while maintaining the high-sensitivity characteristic of the W pixels. PMID:28165425

G-Channel Restoration for RWB CFA with Double-Exposed W Channel.

PubMed

Park, Chulhee; Song, Ki Sun; Kang, Moon Gi

2017-02-05

In this paper, we propose a green (G)-channel restoration for a red-white-blue (RWB) color filter array (CFA) image sensor using the dual sampling technique. By using white (W) pixels instead of G pixels, the RWB CFA provides high-sensitivity imaging and an improved signal-to-noise ratio compared to the Bayer CFA. However, owing to this high sensitivity, the W pixel values become rapidly over-saturated before the red-blue (RB) pixel values reach the appropriate levels. Because the missing G color information included in the W channel cannot be restored with a saturated W, multiple captures with dual sampling are necessary to solve this early W-pixel saturation problem. Each W pixel has a different exposure time when compared to those of the R and B pixels, because the W pixels are double-exposed. Therefore, a RWB-to-RGB color conversion method is required in order to restore the G color information, using a double-exposed W channel. The proposed G-channel restoration algorithm restores G color information from the W channel by considering the energy difference caused by the different exposure times. Using the proposed method, the RGB full-color image can be obtained while maintaining the high-sensitivity characteristic of the W pixels.

Single input state, single–mode fiber–based polarization sensitive optical frequency domain imaging by eigenpolarization referencing

PubMed Central

Lippok, Norman; Villiger, Martin; Jun, Chang–Su; Bouma, Brett E.

2015-01-01

Fiber–based polarization sensitive OFDI is more challenging than free–space implementations. Using multiple input states, fiber–based systems provide sample birefringence information with the benefit of a flexible sample arm but come at the cost of increased system and acquisition complexity, and either reduce acquisition speed or require increased acquisition bandwidth. Here we show that with the calibration of a single polarization state, fiber–based configurations can approach the conceptual simplicity of traditional free–space configurations. We remotely control the polarization state of the light incident at the sample using the eigenpolarization states of a wave plate as a reference, and determine the Jones matrix of the output fiber. We demonstrate this method for polarization sensitive imaging of biological samples. PMID:25927775

Accuracy of imaging methods for detection of bone tissue invasion in patients with oral squamous cell carcinoma

PubMed Central

Uribe, S; Rojas, LA; Rosas, CF

2013-01-01

The objective of this review is to evaluate the diagnostic accuracy of imaging methods for detection of mandibular bone tissue invasion by squamous cell carcinoma (SCC). A systematic review was carried out of studies in MEDLINE, SciELO and ScienceDirect, published between 1960 and 2012, in English, Spanish or German, which compared detection of mandibular bone tissue invasion via different imaging tests against a histopathology reference standard. Sensitivity and specificity data were extracted from each study. The outcome measure was diagnostic accuracy. We found 338 articles, of which 5 fulfilled the inclusion criteria. Tests included were: CT (four articles), MRI (four articles), panoramic radiography (one article), positron emission tomography (PET)/CT (one article) and cone beam CT (CBCT) (one article). The quality of articles was low to moderate and the evidence showed that all tests have a high diagnostic accuracy for detection of mandibular bone tissue invasion by SCC, with sensitivity values of 94% (MRI), 91% (CBCT), 83% (CT) and 55% (panoramic radiography), and specificity values of 100% (CT, MRI, CBCT), 97% (PET/CT) and 91.7% (panoramic radiography). Available evidence is scarce and of only low to moderate quality. However, it is consistently shown that current imaging methods give a moderate to high diagnostic accuracy for the detection of mandibular bone tissue invasion by SCC. Recommendations are given for improving the quality of future reports, in particular provision of a detailed description of the patients' conditions, the imaging instrument and both imaging and histopathological invasion criteria. PMID:23420854

Optimization of digital image processing to determine quantum dots' height and density from atomic force microscopy.

PubMed

Ruiz, J E; Paciornik, S; Pinto, L D; Ptak, F; Pires, M P; Souza, P L

2018-01-01

An optimized method of digital image processing to interpret quantum dots' height measurements obtained by atomic force microscopy is presented. The method was developed by combining well-known digital image processing techniques and particle recognition algorithms. The properties of quantum dot structures strongly depend on dots' height, among other features. Determination of their height is sensitive to small variations in their digital image processing parameters, which can generate misleading results. Comparing the results obtained with two image processing techniques - a conventional method and the new method proposed herein - with the data obtained by determining the height of quantum dots one by one within a fixed area, showed that the optimized method leads to more accurate results. Moreover, the log-normal distribution, which is often used to represent natural processes, shows a better fit to the quantum dots' height histogram obtained with the proposed method. Finally, the quantum dots' height obtained were used to calculate the predicted photoluminescence peak energies which were compared with the experimental data. Again, a better match was observed when using the proposed method to evaluate the quantum dots' height. Copyright © 2017 Elsevier B.V. All rights reserved.

Analysis of painted arts by energy sensitive radiographic techniques with the Pixel Detector Timepix

NASA Astrophysics Data System (ADS)

Zemlicka, J.; Jakubek, J.; Kroupa, M.; Hradil, D.; Hradilova, J.; Mislerova, H.

2011-01-01

Non-invasive techniques utilizing X-ray radiation offer a significant advantage in scientific investigations of painted arts and other cultural artefacts such as painted artworks or statues. In addition, there is also great demand for a mobile analytical and real-time imaging device given the fact that many fine arts cannot be transported. The highly sensitive hybrid semiconductor pixel detector, Timepix, is capable of detecting and resolving subtle and low-contrast differences in the inner composition of a wide variety of objects. Moreover, it is able to map the surface distribution of the contained elements. Several transmission and emission techniques are presented which have been proposed and tested for the analysis of painted artworks. This study focuses on the novel techniques of X-ray transmission radiography (conventional and energy sensitive) and X-ray induced fluorescence imaging (XRF) which can be realised at the table-top scale with the state-of-the-art pixel detector Timepix. Transmission radiography analyses the changes in the X-ray beam intensity caused by specific attenuation of different components in the sample. The conventional approach uses all energies from the source spectrum for the creation of the image while the energy sensitive alternative creates images in given energy intervals which enable identification and separation of materials. The XRF setup is based on the detection of characteristic radiation induced by X-ray photons through a pinhole geometry collimator. The XRF method is extremely sensitive to the material composition but it creates only surface maps of the elemental distribution. For the purpose of the analysis several sets of painted layers have been prepared in a restoration laboratory. The composition of these layers corresponds to those of real historical paintings from the 19th century. An overview of the current status of our methods will be given with respect to the instrumentation and the application in the field of cultural heritage.