Image-Based Predictive Modeling of Heart Mechanics.

PubMed

Wang, V Y; Nielsen, P M F; Nash, M P

2015-01-01

Personalized biophysical modeling of the heart is a useful approach for noninvasively analyzing and predicting in vivo cardiac mechanics. Three main developments support this style of analysis: state-of-the-art cardiac imaging technologies, modern computational infrastructure, and advanced mathematical modeling techniques. In vivo measurements of cardiac structure and function can be integrated using sophisticated computational methods to investigate mechanisms of myocardial function and dysfunction, and can aid in clinical diagnosis and developing personalized treatment. In this article, we review the state-of-the-art in cardiac imaging modalities, model-based interpretation of 3D images of cardiac structure and function, and recent advances in modeling that allow personalized predictions of heart mechanics. We discuss how using such image-based modeling frameworks can increase the understanding of the fundamental biophysics behind cardiac mechanics, and assist with diagnosis, surgical guidance, and treatment planning. Addressing the challenges in this field will require a coordinated effort from both the clinical-imaging and modeling communities. We also discuss future directions that can be taken to bridge the gap between basic science and clinical translation.

SU-F-J-114: On-Treatment Imagereconstruction Using Transit Images of Treatment Beams Through Patient and Thosethrough Planning CT Images

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

Lee, H; Cho, S; Cheong, K

Purpose: To reconstruct patient images at the time of radiation delivery using measured transit images of treatment beams through patient and calculated transit images through planning CT images. Methods: We hypothesize that the ratio of the measured transit images to the calculated images may provide changed amounts of the patient image between times of planning CT and treatment. To test, we have devised lung phantoms with a tumor object (3-cm diameter) placed at iso-center (simulating planning CT) and off-center by 1 cm (simulating treatment). CT images of the two phantoms were acquired; the image of the off-centered phantom, unavailable clinically,more » represents the reference on-treatment image in the image quality of planning CT. Cine-transit images through the two phantoms were also acquired in EPID from a non-modulated 6 MV beam when the gantry was rotated 360 degrees; the image through the centered phantom simulates calculated image. While the current study is a feasibility study, in reality our computational EPID model can be applicable in providing accurate transit image from MC simulation. Changed MV HU values were reconstructed from the ratio between two EPID projection data, converted to KV HU values, and added to the planning CT, thereby reconstructing the on-treatment image of the patient limited to the irradiated region of the phantom. Results: The reconstructed image was compared with the reference image. Except for local HU differences>200 as a maximum, excellent agreement was found. The average difference across the entire image was 16.2 HU. Conclusion: We have demonstrated the feasibility of a method of reconstructing on-treatment images of a patient using EPID image and planning CT images. Further studies will include resolving the local HU differences and investigation on the dosimetry impact of the reconstructed image.« less

Image processing based detection of lung cancer on CT scan images

NASA Astrophysics Data System (ADS)

Abdillah, Bariqi; Bustamam, Alhadi; Sarwinda, Devvi

2017-10-01

In this paper, we implement and analyze the image processing method for detection of lung cancer. Image processing techniques are widely used in several medical problems for picture enhancement in the detection phase to support the early medical treatment. In this research we proposed a detection method of lung cancer based on image segmentation. Image segmentation is one of intermediate level in image processing. Marker control watershed and region growing approach are used to segment of CT scan image. Detection phases are followed by image enhancement using Gabor filter, image segmentation, and features extraction. From the experimental results, we found the effectiveness of our approach. The results show that the best approach for main features detection is watershed with masking method which has high accuracy and robust.

An Analysis of Image Segmentation Time in Beam’s-Eye-View Treatment Planning

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

Li, Chun; Spelbring, D.R.; Chen, George T.Y.

In this work we tabulate and histogram the image segmentation time for beam’s eye view (BEV) treatment planning in our center. The average time needed to generate contours on CT images delineating normal structures and treatment target volumes is calculated using a data base containing over 500 patients’ BEV plans. The average number of contours and total image segmentation time needed for BEV plans in three common treatment sites, namely, head/neck, lung/chest, and prostate, were estimated.

Light on body image treatment: acceptance through mindfulness.

PubMed

Stewart, Tiffany M

2004-11-01

The treatment of body image has to be multifaceted and should be directed toward the treatment of the whole individual-body, mind, and spirit-with an ultimate culmination of acceptance and compassion for the self. This article presents information on a mindful approach to the treatment of body image as it pertains to concerns with body size and shape. This approach fosters the idea that the treatment process should be one of observation, nonjudgment, neutrality, and acceptance. To this end, this article will depict the conceptualization of body image treatment from a mindful perspective, in which mindfulness serves as the foundation on which the multiple facets of treatment are built. The core components of body image treatment (i.e., cognitive, perceptual, behavioral, and emotional), in the context of mindfulness, are discussed as they relate to the treatment of body image disturbance. This article may be viewed as a theoretical overview of a new treatment concept for body image disturbance.

Image-Guided Radiation Therapy: the potential for imaging science research to improve cancer treatment outcomes

NASA Astrophysics Data System (ADS)

Williamson, Jeffrey

2008-03-01

The role of medical imaging in the planning and delivery of radiation therapy (RT) is rapidly expanding. This is being driven by two developments: Image-guided radiation therapy (IGRT) and biological image-based planning (BIBP). IGRT is the systematic use of serial treatment-position imaging to improve geometric targeting accuracy and/or to refine target definition. The enabling technology is the integration of high-performance three-dimensional (3D) imaging systems, e.g., onboard kilovoltage x-ray cone-beam CT, into RT delivery systems. IGRT seeks to adapt the patient's treatment to weekly, daily, or even real-time changes in organ position and shape. BIBP uses non-anatomic imaging (PET, MR spectroscopy, functional MR, etc.) to visualize abnormal tissue biology (angiogenesis, proliferation, metabolism, etc.) leading to more accurate clinical target volume (CTV) delineation and more accurate targeting of high doses to tissue with the highest tumor cell burden. In both cases, the goal is to reduce both systematic and random tissue localization errors (2-5 mm for conventional RT) conformality so that planning target volume (PTV) margins (varying from 8 to 20 mm in conventional RT) used to ensure target volume coverage in the presence of geometric error, can be substantially reduced. Reduced PTV expansion allows more conformal treatment of the target volume, increased avoidance of normal tissue and potential for safe delivery of more aggressive dose regimens. This presentation will focus on the imaging science challenges posed by the IGRT and BIBP. These issues include: Development of robust and accurate nonrigid image-registration (NIR) tools: Extracting locally nonlinear mappings that relate, voxel-by-voxel, one 3D anatomic representation of the patient to differently deformed anatomies acquired at different time points, is essential if IGRT is to move beyond simple translational treatment plan adaptations. NIR is needed to map segmented and labeled anatomy from the

3D fluoroscopic image estimation using patient-specific 4DCBCT-based motion models

PubMed Central

Dhou, Salam; Hurwitz, Martina; Mishra, Pankaj; Cai, Weixing; Rottmann, Joerg; Li, Ruijiang; Williams, Christopher; Wagar, Matthew; Berbeco, Ross; Ionascu, Dan; Lewis, John H.

2015-01-01

3D fluoroscopic images represent volumetric patient anatomy during treatment with high spatial and temporal resolution. 3D fluoroscopic images estimated using motion models built using 4DCT images, taken days or weeks prior to treatment, do not reliably represent patient anatomy during treatment. In this study we develop and perform initial evaluation of techniques to develop patient-specific motion models from 4D cone-beam CT (4DCBCT) images, taken immediately before treatment, and use these models to estimate 3D fluoroscopic images based on 2D kV projections captured during treatment. We evaluate the accuracy of 3D fluoroscopic images by comparing to ground truth digital and physical phantom images. The performance of 4DCBCT- and 4DCT- based motion models are compared in simulated clinical situations representing tumor baseline shift or initial patient positioning errors. The results of this study demonstrate the ability for 4DCBCT imaging to generate motion models that can account for changes that cannot be accounted for with 4DCT-based motion models. When simulating tumor baseline shift and patient positioning errors of up to 5 mm, the average tumor localization error and the 95th percentile error in six datasets were 1.20 and 2.2 mm, respectively, for 4DCBCT-based motion models. 4DCT-based motion models applied to the same six datasets resulted in average tumor localization error and the 95th percentile error of 4.18 and 5.4 mm, respectively. Analysis of voxel-wise intensity differences was also conducted for all experiments. In summary, this study demonstrates the feasibility of 4DCBCT-based 3D fluoroscopic image generation in digital and physical phantoms, and shows the potential advantage of 4DCBCT-based 3D fluoroscopic image estimation when there are changes in anatomy between the time of 4DCT imaging and the time of treatment delivery. PMID:25905722

A MULTICORE BASED PARALLEL IMAGE REGISTRATION METHOD

PubMed Central

Yang, Lin; Gong, Leiguang; Zhang, Hong; Nosher, John L.; Foran, David J.

2012-01-01

Image registration is a crucial step for many image-assisted clinical applications such as surgery planning and treatment evaluation. In this paper we proposed a landmark based nonlinear image registration algorithm for matching 2D image pairs. The algorithm was shown to be effective and robust under conditions of large deformations. In landmark based registration, the most important step is establishing the correspondence among the selected landmark points. This usually requires an extensive search which is often computationally expensive. We introduced a nonregular data partition algorithm using the K-means clustering algorithm to group the landmarks based on the number of available processing cores. The step optimizes the memory usage and data transfer. We have tested our method using IBM Cell Broadband Engine (Cell/B.E.) platform. PMID:19964921

SU-E-P-41: Imaging Coordination of Cone Beam CT, On-Board Image Conjunction with Optical Image Guidance for SBRT Treatment with Respiratory Motion Management

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

Liu, Y; Campbell, J

2015-06-15

Purpose: To spare normal tissue for SBRT lung/liver patients, especially for patients with significant tumor motion, image guided respiratory motion management has been widely implemented in clinical practice. The purpose of this study was to evaluate imaging coordination of cone beam CT, on-board X-ray image conjunction with optical image guidance for SBRT treatment with motion management. Methods: Currently in our clinic a Varian Novlis Tx was utilized for treating SBRT patients implementing CBCT. A BrainLAB X-ray ExacTrac imaging system in conjunction with optical guidance was primarily used for SRS patients. CBCT and X-ray imaging system were independently calibrated with 1.0more » mm tolerance. For SBRT lung/liver patients, the magnitude of tumor motion was measured based-on 4DCT and the measurement was analyzed to determine if patients would be beneficial with respiratory motion management. For patients eligible for motion management, an additional CT with breath holding would be scanned and used as primary planning CT and as reference images for Cone beam CT. During the SBRT treatment, a CBCT with pause and continuing technology would be performed with patients holding breath, which may require 3–4 partially scanned CBCT to combine as a whole CBCT depending on how long patients capable of holding breath. After patients being setup by CBCT images, the ExactTrac X-ray imaging system was implemented with patients’ on-board X-ray images compared to breath holding CT-based DRR. Results: For breath holding patients SBRT treatment, after initially localizing patients with CBCT, we then position patients with ExacTrac X-ray and optical imaging system. The observed deviations of real-time optical guided position average at 3.0, 2.5 and 1.5 mm in longitudinal, vertical and lateral respectively based on 35 treatments. Conclusion: The respiratory motion management clinical practice improved our physician confidence level to give tighter tumor margin for sparing

MR Imaging Based Treatment Planning for Radiotherapy of Prostate Cancer

DTIC Science & Technology

2008-02-01

Radiotherapy, MR-based treatment planning, dosimetry, Monte Carlo dose verification, Prostate Cancer, MRI -based DRRs 16. SECURITY CLASSIFICATION...AcQPlan system Version 5 was used for the study , which is capable of performing dose calculation on both CT and MRI . A four field 3D conformal planning...prostate motion studies for 3DCRT and IMRT of prostate cancer; (2) to investigate and improve the accuracy of MRI -based treatment planning dose calculation

Towards integration of PET/MR hybrid imaging into radiation therapy treatment planning

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

Paulus, Daniel H., E-mail: daniel.paulus@imp.uni-erlangen.de; Thorwath, Daniela; Schmidt, Holger

2014-07-15

Purpose: Multimodality imaging has become an important adjunct of state-of-the-art radiation therapy (RT) treatment planning. Recently, simultaneous PET/MR hybrid imaging has become clinically available and may also contribute to target volume delineation and biological individualization in RT planning. For integration of PET/MR hybrid imaging into RT treatment planning, compatible dedicated RT devices are required for accurate patient positioning. In this study, prototype RT positioning devices intended for PET/MR hybrid imaging are introduced and tested toward PET/MR compatibility and image quality. Methods: A prototype flat RT table overlay and two radiofrequency (RF) coil holders that each fix one flexible body matrixmore » RF coil for RT head/neck imaging have been evaluated within this study. MR image quality with the RT head setup was compared to the actual PET/MR setup with a dedicated head RF coil. PET photon attenuation and CT-based attenuation correction (AC) of the hardware components has been quantitatively evaluated by phantom scans. Clinical application of the new RT setup in PET/MR imaging was evaluated in anin vivo study. Results: The RT table overlay and RF coil holders are fully PET/MR compatible. MR phantom and volunteer imaging with the RT head setup revealed high image quality, comparable to images acquired with the dedicated PET/MR head RF coil, albeit with 25% reduced SNR. Repositioning accuracy of the RF coil holders was below 1 mm. PET photon attenuation of the RT table overlay was calculated to be 3.8% and 13.8% for the RF coil holders. With CT-based AC of the devices, the underestimation error was reduced to 0.6% and 0.8%, respectively. Comparable results were found within the patient study. Conclusions: The newly designed RT devices for hybrid PET/MR imaging are PET and MR compatible. The mechanically rigid design and the reproducible positioning allow for straightforward CT-based AC. The systematic evaluation within this study

SU-F-T-469: A Clinically Observed Discrepancy Between Image-Based and Log- Based MLC Position

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

Neal, B; Ahmed, M; Siebers, J

2016-06-15

Purpose: To present a clinical case which challenges the base assumption of log-file based QA, by showing that the actual position of a MLC leaf can suddenly deviate from its programmed and logged position by >1 mm as observed with real-time imaging. Methods: An EPID-based exit-fluence dosimetry system designed to prevent gross delivery errors was used in cine mode to capture portal images during treatment. Visual monitoring identified an anomalous MLC leaf pair gap not otherwise detected by the automatic position verification. The position of the erred leaf was measured on EPID images and log files were analyzed for themore » treatment in question, the prior day’s treatment, and for daily MLC test patterns acquired on those treatment days. Additional standard test patterns were used to quantify the leaf position. Results: Whereas the log file reported no difference between planned and recorded positions, image-based measurements showed the leaf to be 1.3±0.1 mm medial from the planned position. This offset was confirmed with the test pattern irradiations. Conclusion: It has been clinically observed that log-file derived leaf positions can differ from their actual positions by >1 mm, and therefore cannot be considered to be the actual leaf positions. This cautions the use of log-based methods for MLC or patient quality assurance without independent confirmation of log integrity. Frequent verification of MLC positions through independent means is a necessary precondition to trusting log file records. Intra-treatment EPID imaging provides a method to capture departures from MLC planned positions. Work was supported in part by Varian Medical Systems.« less

Usefulness of image morphing techniques in cancer treatment by conformal radiotherapy

NASA Astrophysics Data System (ADS)

Atoui, Hussein; Sarrut, David; Miguet, Serge

2004-05-01

Conformal radiotherapy is a cancer treatment technique, that targets high-energy X-rays to tumors with minimal exposure to surrounding healthy tissues. Irradiation ballistics is calculated based on an initial 3D Computerized Tomography (CT) scan. At every treatment session, the random positioning of the patient, compared to the reference position defined by the initial 3D CT scan, can generate treatment inaccuracies. Positioning errors potentially predispose to dangerous exposure to healthy tissues as well as insufficient irradiation to the tumor. A proposed solution would be the use of portal images generated by Electronic Portal Imaging Devices (EPID). Portal images (PI) allow a comparison with reference images retained by physicians, namely Digitally Reconstructed Radiographs (DRRs). At present, physicians must estimate patient positional errors by visual inspection. However, this may be inaccurate and consumes time. The automation of this task has been the subject of many researches. Unfortunately, the intensive use of DRRs and the high computing time required have prevented real time implementation. We are currently investigating a new method for DRR generation that calculates intermediate DRRs by 2D deformation of previously computed DRRs. We approach this investigation with the use of a morphing-based technique named mesh warping.

[Value of quantitative iodine-based material decomposition images with gemstone spectral CT imaging in the follow-up of patients with hepatocellular carcinoma after TACE treatment].

PubMed

Xing, Gusheng; Wang, Shuang; Li, Chenrui; Zhao, Xinming; Zhou, Chunwu

2015-03-01

To investigate the value of quantitative iodine-based material decomposition images with gemstone spectral CT imaging in the follow-up of patients with hepatocellular carcinoma (HCC) after transcatheter arterial chemoebolization (TACE). Consecutive 32 HCC patients with previous TACE treatment were included in this study. For the follow-up, arterial phase (AP) and venous phase (VP) dual-phase CT scans were performed with a single-source dual-energy CT scanner (Discovery CT 750HD, GE Healthcare). Iodine concentrations were derived from iodine-based material-decomposition images in the liver parenchyma, tumors and coagulation necrosis (CN) areas. The iodine concentration difference (ICD) between the arterial-phase (AP) and venal-phase (VP) were quantitatively evaluated in different tissues.The lesion-to-normal parenchyma iodine concentration ratio (LNR) was calculated. ROC analysis was performed for the qualitative evaluation, and the area under ROC (Az) was calculated to represent the diagnostic ability of ICD and LNR. In all the 32 HCC patients, the region of interesting (ROI) for iodine concentrations included liver parenchyma (n=42), tumors (n=28) and coagulation necrosis (n=24). During the AP the iodine concentration of CNs (median value 0.088 µg/mm(3)) appeared significantly higher than that of the tumors (0.064 µg/mm(3), P=0.022) and liver parenchyma (0.048 µg/mm(3), P=0.005). But it showed no significant difference between liver parenchyma and tumors (P=0.454). During the VP the iodine concentration in hepatic parenchyma (median value 0.181 µg/mm(3)) was significantly higher than that in CNs (0.140 µg/mm(3), P=0.042). There was no significant difference between liver parenchyma and tumors, CNs and tumors (both P>0.05). The median value of ICD in CNs was 0.006 µg/mm(3), significantly lower than that of the HCC (0.201 µg/mm(3), P<0.001) and hepatic parenchyma (0.117 µg/mm(3), P<0.001). The ICDs in tumors and hepatic parenchyma showed no significant

Imaging Stem Cell Therapy for the Treatment of Peripheral Arterial Disease

PubMed Central

Ransohoff, Julia D.; Wu, Joseph C.

2013-01-01

Arteriosclerotic cardiovascular diseases are among the leading causes of morbidity and mortality worldwide. Therapeutic angiogenesis aims to treat ischemic myocardial and peripheral tissues by delivery of recombinant proteins, genes, or cells to promote neoangiogenesis. Concerns regarding the safety, side effects, and efficacy of protein and gene transfer studies have led to the development of cell-based therapies as alternative approaches to induce vascular regeneration and to improve function of damaged tissue. Cell-based therapies may be improved by the application of imaging technologies that allow investigators to track the location, engraftment, and survival of the administered cell population. The past decade of investigations has produced promising clinical data regarding cell therapy, but design of trials and evaluation of treatments stand to be improved by emerging insight from imaging studies. Here, we provide an overview of pre-clinical and clinical experience using cell-based therapies to promote vascular regeneration in the treatment of peripheral arterial disease. We also review four major imaging modalities and underscore the importance of in vivo analysis of cell fate for a full understanding of functional outcomes. PMID:22239638

[Three-dimensional tooth model reconstruction based on fusion of dental computed tomography images and laser-scanned images].

PubMed

Zhang, Dongxia; Gan, Yangzhou; Xiong, Jing; Xia, Zeyang

2017-02-01

Complete three-dimensional(3D) tooth model provides essential information to assist orthodontists for diagnosis and treatment planning. Currently, 3D tooth model is mainly obtained by segmentation and reconstruction from dental computed tomography(CT) images. However, the accuracy of 3D tooth model reconstructed from dental CT images is low and not applicable for invisalign design. And another serious problem also occurs, i.e. frequentative dental CT scan during different intervals of orthodontic treatment often leads to radiation to the patients. Hence, this paper proposed a method to reconstruct tooth model based on fusion of dental CT images and laser-scanned images. A complete3 D tooth model was reconstructed with the registration and fusion between the root reconstructed from dental CT images and the crown reconstructed from laser-scanned images. The crown of the complete 3D tooth model reconstructed with the proposed method has higher accuracy. Moreover, in order to reconstruct complete 3D tooth model of each orthodontic treatment interval, only one pre-treatment CT scan is needed and in the orthodontic treatment process only the laser-scan is required. Therefore, radiation to the patients can be reduced significantly.

Imaging Surveillance After Primary Breast Cancer Treatment

PubMed Central

Lam, Diana L.; Houssami, Nehmat; Lee, Janie M.

2017-01-01

OBJECTIVE Current clinical guidelines are consistent in supporting annual mammography for women after treatment of primary breast cancer. Surveillance imaging beyond standard digital mammography, including digital breast tomosynthesis (DBT), breast ultrasound, and MRI, may improve outcomes. This article reviews the evidence on the performance and effectiveness of breast imaging modalities available for surveillance after treatment of sporadic unilateral primary breast cancer and identifies additional factors to be considered when selecting an imaging surveillance regimen. CONCLUSION Evidence review supports the use of mammography for surveillance after primary breast cancer treatment. Variability exists in guideline recommendations for surveillance initiation, interval, and cessation. DBT offers the most promise as a potential modality to replace standard digital mammography as a front-line surveillance test; a single published study to date has shown a significant decrease in recall rates compared with standard digital mammography alone. Most guidelines do not support the use of whole-breast ultrasound in breast cancer surveillance, and further studies are needed to define the characteristics of women who may benefit from MRI surveillance. The emerging evidence about surveillance imaging outcomes suggests that additional factors, including patient and imaging characteristics, tumor biology and gene expression profile, and choice of treatment, warrant consideration in selecting personalized posttreatment imaging surveillance regimens. PMID:28075622

Analysis of image heterogeneity using 2D Minkowski functionals detects tumor responses to treatment.

PubMed

Larkin, Timothy J; Canuto, Holly C; Kettunen, Mikko I; Booth, Thomas C; Hu, De-En; Krishnan, Anant S; Bohndiek, Sarah E; Neves, André A; McLachlan, Charles; Hobson, Michael P; Brindle, Kevin M

2014-01-01

The acquisition of ever increasing volumes of high resolution magnetic resonance imaging (MRI) data has created an urgent need to develop automated and objective image analysis algorithms that can assist in determining tumor margins, diagnosing tumor stage, and detecting treatment response. We have shown previously that Minkowski functionals, which are precise morphological and structural descriptors of image heterogeneity, can be used to enhance the detection, in T1 -weighted images, of a targeted Gd(3+) -chelate-based contrast agent for detecting tumor cell death. We have used Minkowski functionals here to characterize heterogeneity in T2 -weighted images acquired before and after drug treatment, and obtained without contrast agent administration. We show that Minkowski functionals can be used to characterize the changes in image heterogeneity that accompany treatment of tumors with a vascular disrupting agent, combretastatin A4-phosphate, and with a cytotoxic drug, etoposide. Parameterizing changes in the heterogeneity of T2 -weighted images can be used to detect early responses of tumors to drug treatment, even when there is no change in tumor size. The approach provides a quantitative and therefore objective assessment of treatment response that could be used with other types of MR image and also with other imaging modalities. Copyright © 2013 Wiley Periodicals, Inc.

Radiotherapy supporting system based on the image database using IS&C magneto-optical disk

NASA Astrophysics Data System (ADS)

Ando, Yutaka; Tsukamoto, Nobuhiro; Kunieda, Etsuo; Kubo, Atsushi

1994-05-01

Since radiation oncologists make the treatment plan by prior experience, information about previous cases is helpful in planning the radiation treatment. We have developed an supporting system for the radiation therapy. The case-based reasoning method was implemented in order to search old treatments and images of past cases. This system evaluates similarities between the current case and all stored cases (case base). The portal images of the similar cases can be retrieved for reference images, as well as treatment records which show examples of the radiation treatment. By this system radiotherapists can easily make suitable plans of the radiation therapy. This system is useful to prevent inaccurate plannings due to preconceptions and/or lack of knowledge. Images were stored into magneto-optical disks and the demographic data is recorded to the hard disk which is equipped in the personal computer. Images can be displayed quickly on the radiotherapist's demands. The radiation oncologist can refer past cases which are recorded in the case base and decide the radiation treatment of the current case. The file and data format of magneto-optical disk is the IS&C format. This format provides the interchangeability and reproducibility of the medical information which includes images and other demographic data.

Digital diagnosis and treatment of mandibular condylar fractures based on Extensible Neuro imaging Archive Toolkit (XNAT)

PubMed Central

Ren, Jiayin; He, Mingyun; Huang, Yongqing; Tian, WeiDong; Tang, Wei

2018-01-01

Objectives The treatment of condylar fractures has long been controversial. In this paper, we established a database for accurate measurement, storage, management and analysis of patients’ data, in order to help determine the best treatment plan. Methods First of all, the diagnosis and treatment database was established based on XNAT, including 339 cases of condylar fractures and their related information. Then image segmentation, registration and three-dimensional (3D) measurement were used to measure and analyze the condyle shapes. Statistical analysis was used to analyze the anatomical structure changes of condyle and the surrounding tissues at different stages before and after treatment. The processes of condylar fracture reestablishment at different stages were also dynamically monitored. Finally, based on all these information, the digital diagnosis and treatment plans for condylar fractures were developed. Results For the patients less than 18 years old with no significant dislocation, surgical treatment and conservative treatment were equally effective for intracapsular fracture, and had no significant difference for neck and basal fractures. For patients above 18 years old, there was no significant difference between the two treatment methods for intracapsular fractures; but for condylar neck and basal fractures, surgical treatment was better than conservative treatment. When condylar fracture shift angle was greater than 11 degrees, and mandibular ramus height reduction was greater than 4mm, the patients felt the strongest pain, and their mouths opening was severely restricted. There were 170 surgical cases with condylar fracture shift angel greater than 11 degrees, and 118 of them (69.4%) had good prognosis, 52 of them (30.6%) had complications such as limited mouth opening. There were 173 surgical cases with mandibular ramus height reduction more than 4mm, and 112 of them (64.7%) had good prognosis, 61 of them (35.3%) had complications such as limited

Clinical efficacy and safety of surface imaging guided radiosurgery (SIG-RS) in the treatment of benign skull base tumors.

PubMed

Lau, Steven K M; Patel, Kunal; Kim, Teddy; Knipprath, Erik; Kim, Gwe-Ya; Cerviño, Laura I; Lawson, Joshua D; Murphy, Kevin T; Sanghvi, Parag; Carter, Bob S; Chen, Clark C

2017-04-01

Frameless, surface imaging guided radiosurgery (SIG-RS) is a novel platform for stereotactic radiosurgery (SRS) wherein patient positioning is monitored in real-time through infra-red camera tracking of facial topography. Here we describe our initial clinical experience with SIG-RS for the treatment of benign neoplasms of the skull base. We identified 48 patients with benign skull base tumors consecutively treated with SIG-RS at a single institution between 2009 and 2011. Patients were diagnosed with meningioma (n = 22), vestibular schwannoma (n = 20), or nonfunctional pituitary adenoma (n = 6). Local control and treatment-related toxicity were retrospectively assessed. Median follow-up was 65 months (range 61-72 months). Prescription doses were 12-13 Gy in a single fraction (n = 18), 8 Gy × 3 fractions (n = 6), and 5 Gy × 5 fractions (n = 24). Actuarial tumor control rate at 5 years was 98%. No grade ≥3 treatment-related toxicity was observed. Grade ≤2 toxicity was associated with symptomatic lesions (p = 0.049) and single fraction treatment (p = 0.005). SIG-RS for benign skull base tumors produces clinical outcomes comparable to conventional frame-based SRS techniques while enhancing patient comfort.

Remote Cherenkov imaging-based quality assurance of a magnetic resonance image-guided radiotherapy system.

PubMed

Andreozzi, Jacqueline M; Mooney, Karen E; Brůža, Petr; Curcuru, Austen; Gladstone, David J; Pogue, Brian W; Green, Olga

2018-06-01

Tools to perform regular quality assurance of magnetic resonance image-guided radiotherapy (MRIgRT) systems should ideally be independent of interference from the magnetic fields. Remotely acquired optical Cherenkov imaging-based dosimetry measurements in water were investigated for this purpose, comparing measures of dose accuracy, temporal dynamics, and overall integrated IMRT delivery. A 40 × 30.5 × 37.5 cm 3 water tank doped with 1 g/L of quinine sulfate was imaged using an intensified charge-coupled device (ICCD) to capture the Cherenkov emission while being irradiated by a commercial MRIgRT system (ViewRay™). The ICCD was placed down-bore at the end of the couch, 4 m from treatment isocenter and behind the 5-Gauss line of the 0.35-T MRI. After establishing optimal camera acquisition settings, square beams of increasing size (4.2 × 4.2 cm 2 , 10.5 × 10.5 cm 2 , and 14.7 × 14.7 cm 2 ) were imaged at 0.93 frames per second, from an individual cobalt-60 treatment head, to develop projection measures related to percent depth dose (PDD) curves and cross beam profiles (CPB). These Cherenkov-derived measurements were compared to ionization chamber (IC) and radiographic film dosimetry data, as well as simulation data from the treatment planning system (TPS). An intensity-modulated radiotherapy (IMRT) commissioning plan from AAPM TG-119 (C4:C-Shape) was also imaged at 2.1 frames per second, and the single linear sum image from 509 s of plan delivery was compared to the dose volume prediction generated by the TPS using gamma index analysis. Analysis of standardized test target images (1024 × 1024 pixels) yielded a pixel resolution of 0.37 mm/pixel. The beam width measured from the Cherenkov image-generated projection CBPs was within 1 mm accuracy when compared to film measurements for all beams. The 502 point measurements (i.e., pixels) of the Cherenkov image-based projection percent depth dose curves (pPDDs) were compared to p

Harmonic Motion Imaging (HMI) for Tumor Imaging and Treatment Monitoring.

PubMed

Konofagou, Elisa E; Maleke, Caroline; Vappou, Jonathan

2012-01-01

Palpation is an established screening procedure for the detection of several superficial cancers including breast, thyroid, prostate, and liver tumors through both self and clinical examinations. This is because solid masses typically have distinct stiffnesses compared to the surrounding normal tissue. In this paper, the application of Harmonic Motion Imaging (HMI) for tumor detection based on its stiffness as well as its relevance in thermal treatment is reviewed. HMI uses a focused ultrasound (FUS) beam to generate an oscillatory acoustic radiation force for an internal, non-contact palpation to internally estimate relative tissue hardness. HMI studies have dealt with the measurement of the tissue dynamic motion in response to an oscillatory acoustic force at the same frequency, and have been shown feasible in simulations, phantoms, ex vivo human and bovine tissues as well as animals in vivo. Using an FUS beam, HMI can also be used in an ideal integration setting with thermal ablation using high-intensity focused ultrasound (HIFU), which also leads to an alteration in the tumor stiffness. In this paper, a short review of HMI is provided that encompasses the findings in all the aforementioned areas. The findings presented herein demonstrate that the HMI displacement can accurately depict the underlying tissue stiffness, and the HMI image of the relative stiffness could accurately detect and characterize the tumor or thermal lesion based on its distinct properties. HMI may thus constitute a non-ionizing, cost-efficient and reliable complementary method for noninvasive tumor detection, localization, diagnosis and treatment monitoring.

Harmonic Motion Imaging (HMI) for Tumor Imaging and Treatment Monitoring

PubMed Central

Maleke, Caroline; Vappou, Jonathan

2014-01-01

Palpation is an established screening procedure for the detection of several superficial cancers including breast, thyroid, prostate, and liver tumors through both self and clinical examinations. This is because solid masses typically have distinct stiffnesses compared to the surrounding normal tissue. In this paper, the application of Harmonic Motion Imaging (HMI) for tumor detection based on its stiffness as well as its relevance in thermal treatment is reviewed. HMI uses a focused ultrasound (FUS) beam to generate an oscillatory acoustic radiation force for an internal, non-contact palpation to internally estimate relative tissue hardness. HMI studies have dealt with the measurement of the tissue dynamic motion in response to an oscillatory acoustic force at the same frequency, and have been shown feasible in simulations, phantoms, ex vivo human and bovine tissues as well as animals in vivo. Using an FUS beam, HMI can also be used in an ideal integration setting with thermal ablation using high-intensity focused ultrasound (HIFU), which also leads to an alteration in the tumor stiffness. In this paper, a short review of HMI is provided that encompasses the findings in all the aforementioned areas. The findings presented herein demonstrate that the HMI displacement can accurately depict the underlying tissue stiffness, and the HMI image of the relative stiffness could accurately detect and characterize the tumor or thermal lesion based on its distinct properties. HMI may thus constitute a non-ionizing, cost-efficient and reliable complementary method for noninvasive tumor detection, localization, diagnosis and treatment monitoring. PMID:25364321

Impact of region contouring variability on image-based focal therapy evaluation

NASA Astrophysics Data System (ADS)

Gibson, Eli; Donaldson, Ian A.; Shah, Taimur T.; Hu, Yipeng; Ahmed, Hashim U.; Barratt, Dean C.

2016-03-01

Motivation: Focal therapy is an emerging low-morbidity treatment option for low-intermediate risk prostate cancer; however, challenges remain in accurately delivering treatment to specified targets and determining treatment success. Registered multi-parametric magnetic resonance imaging (MPMRI) acquired before and after treatment can support focal therapy evaluation and optimization; however, contouring variability, when defining the prostate, the clinical target volume (CTV) and the ablation region in images, reduces the precision of quantitative image-based focal therapy evaluation metrics. To inform the interpretation and clarify the limitations of such metrics, we investigated inter-observer contouring variability and its impact on four metrics. Methods: Pre-therapy and 2-week-post-therapy standard-of-care MPMRI were acquired from 5 focal cryotherapy patients. Two clinicians independently contoured, on each slice, the prostate (pre- and post-treatment) and the dominant index lesion CTV (pre-treatment) in the T2-weighted MRI, and the ablated region (post-treatment) in the dynamic-contrast- enhanced MRI. For each combination of clinician contours, post-treatment images were registered to pre-treatment images using a 3D biomechanical-model-based registration of prostate surfaces, and four metrics were computed: the proportion of the target tissue region that was ablated and the target:ablated region volume ratio for each of two targets (the CTV and an expanded planning target volume). Variance components analysis was used to measure the contribution of each type of contour to the variance in the therapy evaluation metrics. Conclusions: 14-23% of evaluation metric variance was attributable to contouring variability (including 6-12% from ablation region contouring); reducing this variability could improve the precision of focal therapy evaluation metrics.

Simulation of pseudo-CT images based on deformable image registration of ultrasound images: A proof of concept for transabdominal ultrasound imaging of the prostate during radiotherapy

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

Meer, Skadi van der; Camps, Saskia M.; Oncology Solutions Department, Philips Research, High Tech Campus 34, Eindhoven 5656 AE

Purpose: Imaging of patient anatomy during treatment is a necessity for position verification and for adaptive radiotherapy based on daily dose recalculation. Ultrasound (US) image guided radiotherapy systems are currently available to collect US images at the simulation stage (US{sub sim}), coregistered with the simulation computed tomography (CT), and during all treatment fractions. The authors hypothesize that a deformation field derived from US-based deformable image registration can be used to create a daily pseudo-CT (CT{sub ps}) image that is more representative of the patients’ geometry during treatment than the CT acquired at simulation stage (CT{sub sim}). Methods: The three prostatemore » patients, considered to evaluate this hypothesis, had coregistered CT and US scans on various days. In particular, two patients had two US–CT datasets each and the third one had five US–CT datasets. Deformation fields were computed between pairs of US images of the same patient and then applied to the corresponding US{sub sim} scan to yield a new deformed CT{sub ps} scan. The original treatment plans were used to recalculate dose distributions in the simulation, deformed and ground truth CT (CT{sub gt}) images to compare dice similarity coefficients, maximum absolute distance, and mean absolute distance on CT delineations and gamma index (γ) evaluations on both the Hounsfield units (HUs) and the dose. Results: In the majority, deformation did improve the results for all three evaluation methods. The change in gamma failure for dose (γ{sub Dose}, 3%, 3 mm) ranged from an improvement of 11.2% in the prostate volume to a deterioration of 1.3% in the prostate and bladder. The change in gamma failure for the CT images (γ{sub CT}, 50 HU, 3 mm) ranged from an improvement of 20.5% in the anus and rectum to a deterioration of 3.2% in the prostate. Conclusions: This new technique may generate CT{sub ps} images that are more representative of the actual patient anatomy

Image registration assessment in radiotherapy image guidance based on control chart monitoring.

PubMed

Xia, Wenyao; Breen, Stephen L

2018-04-01

Image guidance with cone beam computed tomography in radiotherapy can guarantee the precision and accuracy of patient positioning prior to treatment delivery. During the image guidance process, operators need to take great effort to evaluate the image guidance quality before correcting a patient's position. This work proposes an image registration assessment method based on control chart monitoring to reduce the effort taken by the operator. According to the control chart plotted by daily registration scores of each patient, the proposed method can quickly detect both alignment errors and image quality inconsistency. Therefore, the proposed method can provide a clear guideline for the operators to identify unacceptable image quality and unacceptable image registration with minimal effort. Experimental results demonstrate that by using control charts from a clinical database of 10 patients undergoing prostate radiotherapy, the proposed method can quickly identify out-of-control signals and find special cause of out-of-control registration events.

Light on Body Image Treatment: Acceptance Through Mindfulness

ERIC Educational Resources Information Center

Stewart, Tiffany M.

2004-01-01

The treatment of body image has to be multifaceted and should be directed toward the treatment of the whole individual - body, mind, and spirit - with an ultimate culmination of acceptance and compassion for the self. This article presents information on a mindful approach to the treatment of body image as it pertains to concerns with body size…

Non-invasive, photonics-based diagnostic, imaging, monitoring, and light delivery techniques for the recognition, quantification and treatment of malignant and chronic inflammatory conditions

NASA Astrophysics Data System (ADS)

Davies, N.; Davies-Shaw, D.; Shaw, J. D.

2007-02-01

We report firsthand on innovative developments in non-invasive, biophotonic techniques for a wide range of diagnostic, imaging and treatment options, including the recognition and quantification of cancerous, pre-cancerous cells and chronic inflammatory conditions. These techniques have benefited from the ability to target the affected site by both monochromatic light and broad multiple wavelength spectra. The employment of such wavelength or color-specific properties embraces the fluorescence stimulation of various photosensitizing drugs, and the instigation and detection of identified fluorescence signatures attendant upon laser induced fluorescence (LIF) phenomena as transmitted and propagated by precancerous, cancerous and normal tissue. In terms of tumor imaging and therapeutic and treatment options, we have exploited the abilities of various wavelengths to penetrate to different depths, through different types of tissues, and have explored quantifiable absorption and reflection characteristics upon which diagnostic assumptions can be reliably based and formulated. These biophotonic-based diagnostic, sensing and imaging techniques have also benefited from, and have been further enhanced by, the integrated ability to provide various power levels to be employed at various stages in the procedure. Applications are myriad, including non-invasive, non destructive diagnosis of in vivo cell characteristics and functions; light-based tissue analysis; real-time monitoring and mapping of brain function and of tumor growth; real time monitoring of the surgical completeness of tumor removal during laser-imaged/guided brain resection; diagnostic procedures based on fluorescence life-time monitoring, the monitoring of chronic inflammatory conditions (including rheumatoid arthritis), and continuous blood glucose monitoring in the control of diabetes.

Research of flaw image collecting and processing technology based on multi-baseline stereo imaging

NASA Astrophysics Data System (ADS)

Yao, Yong; Zhao, Jiguang; Pang, Xiaoyan

2008-03-01

Aiming at the practical situations such as accurate optimal design, complex algorithms and precise technical demands of gun bore flaw image collecting, the design frame of a 3-D image collecting and processing system based on multi-baseline stereo imaging was presented in this paper. This system mainly including computer, electrical control box, stepping motor and CCD camera and it can realize function of image collection, stereo matching, 3-D information reconstruction and after-treatments etc. Proved by theoretical analysis and experiment results, images collected by this system were precise and it can slake efficiently the uncertainty problem produced by universally veins or repeated veins. In the same time, this system has faster measure speed and upper measure precision.

Content-based image retrieval from a database of fracture images

NASA Astrophysics Data System (ADS)

Müller, Henning; Do Hoang, Phuong Anh; Depeursinge, Adrien; Hoffmeyer, Pierre; Stern, Richard; Lovis, Christian; Geissbuhler, Antoine

2007-03-01

This article describes the use of a medical image retrieval system on a database of 16'000 fractures, selected from surgical routine over several years. Image retrieval has been a very active domain of research for several years. It was frequently proposed for the medical domain, but only few running systems were ever tested in clinical routine. For the planning of surgical interventions after fractures, x-ray images play an important role. The fractures are classified according to exact fracture location, plus whether and to which degree the fracture is damaging articulations to see how complicated a reparation will be. Several classification systems for fractures exist and the classification plus the experience of the surgeon lead in the end to the choice of surgical technique (screw, metal plate, ...). This choice is strongly influenced by the experience and knowledge of the surgeons with respect to a certain technique. Goal of this article is to describe a prototype that supplies similar cases to an example to help treatment planning and find the most appropriate technique for a surgical intervention. Our database contains over 16'000 fracture images before and after a surgical intervention. We use an image retrieval system (GNU Image Finding Tool, GIFT) to find cases/images similar to an example case currently under observation. Problems encountered are varying illumination of images as well as strong anatomic differences between patients. Regions of interest are usually small and the retrieval system needs to focus on this region. Results show that GIFT is capable of supplying similar cases, particularly when using relevance feedback, on such a large database. Usual image retrieval is based on a single image as search target but for this application we have to select images by case as similar cases need to be found and not images. A few false positive cases often remain in the results but they can be sorted out quickly by the surgeons. Image retrieval can

Skull base, orbits, temporal bone, and cranial nerves: anatomy on MR imaging.

PubMed

Morani, Ajaykumar C; Ramani, Nisha S; Wesolowski, Jeffrey R

2011-08-01

Accurate delineation, diagnosis, and treatment planning of skull base lesions require knowledge of the complex anatomy of the skull base. Because the skull base cannot be directly evaluated, imaging is critical for the diagnosis and management of skull base diseases. Although computed tomography (CT) is excellent for outlining the bony detail, magnetic resonance (MR) imaging provides better soft tissue detail and is helpful for evaluating the adjacent meninges, brain parenchyma, and bone marrow of the skull base. Thus, CT and MR imaging are often used together for evaluating skull base lesions. This article focuses on the radiologic anatomy of the skull base pertinent to MR imaging evaluation. Copyright © 2011 Elsevier Inc. All rights reserved.

Clinical application of in vivo treatment delivery verification based on PET/CT imaging of positron activity induced at high energy photon therapy

NASA Astrophysics Data System (ADS)

Janek Strååt, Sara; Andreassen, Björn; Jonsson, Cathrine; Noz, Marilyn E.; Maguire, Gerald Q., Jr.; Näfstadius, Peder; Näslund, Ingemar; Schoenahl, Frederic; Brahme, Anders

2013-08-01

The purpose of this study was to investigate in vivo verification of radiation treatment with high energy photon beams using PET/CT to image the induced positron activity. The measurements of the positron activation induced in a preoperative rectal cancer patient and a prostate cancer patient following 50 MV photon treatments are presented. A total dose of 5 and 8 Gy, respectively, were delivered to the tumors. Imaging was performed with a 64-slice PET/CT scanner for 30 min, starting 7 min after the end of the treatment. The CT volume from the PET/CT and the treatment planning CT were coregistered by matching anatomical reference points in the patient. The treatment delivery was imaged in vivo based on the distribution of the induced positron emitters produced by photonuclear reactions in tissue mapped on to the associated dose distribution of the treatment plan. The results showed that spatial distribution of induced activity in both patients agreed well with the delivered beam portals of the treatment plans in the entrance subcutaneous fat regions but less so in blood and oxygen rich soft tissues. For the preoperative rectal cancer patient however, a 2 ± (0.5) cm misalignment was observed in the cranial-caudal direction of the patient between the induced activity distribution and treatment plan, indicating a beam patient setup error. No misalignment of this kind was seen in the prostate cancer patient. However, due to a fast patient setup error in the PET/CT scanner a slight mis-position of the patient in the PET/CT was observed in all three planes, resulting in a deformed activity distribution compared to the treatment plan. The present study indicates that the induced positron emitters by high energy photon beams can be measured quite accurately using PET imaging of subcutaneous fat to allow portal verification of the delivered treatment beams. Measurement of the induced activity in the patient 7 min after receiving 5 Gy involved count rates which were about

An artificial neural networks approach for assessment treatment response in oncological patients using PET/CT images.

PubMed

Nogueira, Mariana A; Abreu, Pedro H; Martins, Pedro; Machado, Penousal; Duarte, Hugo; Santos, João

2017-02-13

Positron Emission Tomography - Computed Tomography (PET/CT) imaging is the basis for the evaluation of response-to-treatment of several oncological diseases. In practice, such evaluation is manually performed by specialists, which is rather complex and time-consuming. Evaluation measures have been proposed, but with questionable reliability. The usage of before and after-treatment image descriptors of the lesions for treatment response evaluation is still a territory to be explored. In this project, Artificial Neural Network approaches were implemented to automatically assess treatment response of patients suffering from neuroendocrine tumors and Hodgkyn lymphoma, based on image features extracted from PET/CT. The results show that the considered set of features allows for the achievement of very high classification performances, especially when data is properly balanced. After synthetic data generation and PCA-based dimensionality reduction to only two components, LVQNN assured classification accuracies of 100%, 100%, 96.3% and 100% regarding the 4 response-to-treatment classes.

WE-G-207-06: 3D Fluoroscopic Image Generation From Patient-Specific 4DCBCT-Based Motion Models Derived From Physical Phantom and Clinical Patient Images

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

Dhou, S; Cai, W; Hurwitz, M

2015-06-15

Purpose: Respiratory-correlated cone-beam CT (4DCBCT) images acquired immediately prior to treatment have the potential to represent patient motion patterns and anatomy during treatment, including both intra- and inter-fractional changes. We develop a method to generate patient-specific motion models based on 4DCBCT images acquired with existing clinical equipment and used to generate time varying volumetric images (3D fluoroscopic images) representing motion during treatment delivery. Methods: Motion models are derived by deformably registering each 4DCBCT phase to a reference phase, and performing principal component analysis (PCA) on the resulting displacement vector fields. 3D fluoroscopic images are estimated by optimizing the resulting PCAmore » coefficients iteratively through comparison of the cone-beam projections simulating kV treatment imaging and digitally reconstructed radiographs generated from the motion model. Patient and physical phantom datasets are used to evaluate the method in terms of tumor localization error compared to manually defined ground truth positions. Results: 4DCBCT-based motion models were derived and used to generate 3D fluoroscopic images at treatment time. For the patient datasets, the average tumor localization error and the 95th percentile were 1.57 and 3.13 respectively in subsets of four patient datasets. For the physical phantom datasets, the average tumor localization error and the 95th percentile were 1.14 and 2.78 respectively in two datasets. 4DCBCT motion models are shown to perform well in the context of generating 3D fluoroscopic images due to their ability to reproduce anatomical changes at treatment time. Conclusion: This study showed the feasibility of deriving 4DCBCT-based motion models and using them to generate 3D fluoroscopic images at treatment time in real clinical settings. 4DCBCT-based motion models were found to account for the 3D non-rigid motion of the patient anatomy during treatment and have the

MO-F-CAMPUS-J-02: Automatic Recognition of Patient Treatment Site in Portal Images Using Machine Learning

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

Chang, X; Yang, D

Purpose: To investigate the method to automatically recognize the treatment site in the X-Ray portal images. It could be useful to detect potential treatment errors, and to provide guidance to sequential tasks, e.g. automatically verify the patient daily setup. Methods: The portal images were exported from MOSAIQ as DICOM files, and were 1) processed with a threshold based intensity transformation algorithm to enhance contrast, and 2) where then down-sampled (from 1024×768 to 128×96) by using bi-cubic interpolation algorithm. An appearance-based vector space model (VSM) was used to rearrange the images into vectors. A principal component analysis (PCA) method was usedmore » to reduce the vector dimensions. A multi-class support vector machine (SVM), with radial basis function kernel, was used to build the treatment site recognition models. These models were then used to recognize the treatment sites in the portal image. Portal images of 120 patients were included in the study. The images were selected to cover six treatment sites: brain, head and neck, breast, lung, abdomen and pelvis. Each site had images of the twenty patients. Cross-validation experiments were performed to evaluate the performance. Results: MATLAB image processing Toolbox and scikit-learn (a machine learning library in python) were used to implement the proposed method. The average accuracies using the AP and RT images separately were 95% and 94% respectively. The average accuracy using AP and RT images together was 98%. Computation time was ∼0.16 seconds per patient with AP or RT image, ∼0.33 seconds per patient with both of AP and RT images. Conclusion: The proposed method of treatment site recognition is efficient and accurate. It is not sensitive to the differences of image intensity, size and positions of patients in the portal images. It could be useful for the patient safety assurance. The work was partially supported by a research grant from Varian Medical System.« less

A survey of GPU-based medical image computing techniques

PubMed Central

Shi, Lin; Liu, Wen; Zhang, Heye; Xie, Yongming

2012-01-01

Medical imaging currently plays a crucial role throughout the entire clinical applications from medical scientific research to diagnostics and treatment planning. However, medical imaging procedures are often computationally demanding due to the large three-dimensional (3D) medical datasets to process in practical clinical applications. With the rapidly enhancing performances of graphics processors, improved programming support, and excellent price-to-performance ratio, the graphics processing unit (GPU) has emerged as a competitive parallel computing platform for computationally expensive and demanding tasks in a wide range of medical image applications. The major purpose of this survey is to provide a comprehensive reference source for the starters or researchers involved in GPU-based medical image processing. Within this survey, the continuous advancement of GPU computing is reviewed and the existing traditional applications in three areas of medical image processing, namely, segmentation, registration and visualization, are surveyed. The potential advantages and associated challenges of current GPU-based medical imaging are also discussed to inspire future applications in medicine. PMID:23256080

Calcium-based biomaterials for diagnosis, treatment, and theranostics.

PubMed

Qi, Chao; Lin, Jing; Fu, Lian-Hua; Huang, Peng

2018-01-22

Calcium-based (CaXs) biomaterials including calcium phosphates, calcium carbonates, calcium silicate and calcium fluoride have been widely utilized in the biomedical field owing to their excellent biocompatibility and biodegradability. In recent years, CaXs biomaterials have been strategically integrated with imaging contrast agents and therapeutic agents for various molecular imaging modalities including fluorescence imaging, magnetic resonance imaging, ultrasound imaging or multimodal imaging, as well as for various therapeutic approaches including chemotherapy, gene therapy, hyperthermia therapy, photodynamic therapy, radiation therapy, or combination therapy, even imaging-guided therapy. Compared with other inorganic biomaterials such as silica-, carbon-, and gold-based biomaterials, CaXs biomaterials can dissolve into nontoxic ions and participate in the normal metabolism of organisms. Thus, they offer safer clinical solutions for disease theranostics. This review focuses on the state-of-the-art progress in CaXs biomaterials, which covers from their categories, characteristics and preparation methods to their bioapplications including diagnosis, treatment, and theranostics. Moreover, the current trends and key problems as well as the future prospects and challenges of CaXs biomaterials are also discussed at the end.

Earlier Detection of Tumor Treatment Response Using Magnetic Resonance Diffusion Imaging with Oscillating Gradients

PubMed Central

Colvin, Daniel C.; Loveless, Mary E.; Does, Mark D.; Yue, Zou; Yankeelov, Thomas E.; Gore, John C.

2011-01-01

An improved method for detecting early changes in tumors in response to treatment, based on a modification of diffusion-weighted magnetic resonance imaging, has been demonstrated in an animal model. Early detection of therapeutic response in tumors is important both clinically and in pre-clinical assessments of novel treatments. Non-invasive imaging methods that can detect and assess tumor response early in the course of treatment, and before frank changes in tumor morphology are evident, are of considerable interest as potential biomarkers of treatment efficacy. Diffusion-weighted magnetic resonance imaging is sensitive to changes in water diffusion rates in tissues that result from structural variations in the local cellular environment, but conventional methods mainly reflect changes in tissue cellularity and do not convey information specific to micro-structural variations at sub-cellular scales. We implemented a modified imaging technique using oscillating gradients of the magnetic field for evaluating water diffusion rates over very short spatial scales that are more specific for detecting changes in intracellular structure that may precede changes in cellularity. Results from a study of orthotopic 9L gliomas in rat brains indicate that this method can detect changes as early as 24 hours following treatment with 1,3-bis(2-chloroethyl)-1-nitrosourea (BCNU), when conventional approaches do not find significant effects. These studies suggest that diffusion imaging using oscillating gradients may be used to obtain an earlier indication of treatment efficacy than previous magnetic resonance imaging methods. PMID:21190804

TU-D-207B-03: Early Assessment of Response to Chemoradiotherapy Based On Textural Analysis of Pre and Mid-Treatment FDG-PET Image in Locally Advanced Head and Neck Cancer

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

Cui, Y; Pollom, E; Loo, B

Purpose: To evaluate whether tumor textural features extracted from both pre- and mid-treatment FDG-PET images predict early response to chemoradiotherapy in locally advanced head and neck cancer, and investigate whether they provide complementary value to conventional volume-based measurements. Methods: Ninety-four patients with locally advanced head and neck cancers were retrospectively studied. All patients received definitive chemoradiotherapy and underwent FDG-PET planning scans both before and during treatment. Within the primary tumor we extracted 6 textural features based on gray-level co-occurrence matrices (GLCM): entropy, dissimilarity, contrast, correlation, energy, and homogeneity. These image features were evaluated for their predictive power of treatment responsemore » to chemoradiotherapy in terms of local recurrence free survival (LRFS) and progression free survival (PFS). Logrank test were used to assess the statistical significance of the stratification between low- and high-risk groups. P-values were adjusted for multiple comparisons by the false discovery rate (FDR) method. Results: All six textural features extracted from pre-treatment PET images significantly differentiated low- and high-risk patient groups for LRFS (P=0.011–0.038) and PFS (P=0.029–0.034). On the other hand, none of the textural features on mid-treatment PET images was statistically significant in stratifying LRFS (P=0.212–0.445) or PFS (P=0.168–0.299). An imaging signature that combines textural feature (GLCM homogeneity) and metabolic tumor volume showed an improved performance for predicting LRFS (hazard ratio: 22.8, P<0.0001) and PFS (hazard ratio: 13.9, P=0.0005) in leave-one-out cross validation. Intra-tumor heterogeneity measured by textural features was significantly lower in mid-treatment PET images than in pre-treatment PET images (T-test: P<1.4e-6). Conclusion: Tumor textural features on pretreatment FDG-PET images are predictive for response to

A feasibility study of treatment verification using EPID cine images for hypofractionated lung radiotherapy

NASA Astrophysics Data System (ADS)

Tang, Xiaoli; Lin, Tong; Jiang, Steve

2009-09-01

We propose a novel approach for potential online treatment verification using cine EPID (electronic portal imaging device) images for hypofractionated lung radiotherapy based on a machine learning algorithm. Hypofractionated radiotherapy requires high precision. It is essential to effectively monitor the target to ensure that the tumor is within the beam aperture. We modeled the treatment verification problem as a two-class classification problem and applied an artificial neural network (ANN) to classify the cine EPID images acquired during the treatment into corresponding classes—with the tumor inside or outside of the beam aperture. Training samples were generated for the ANN using digitally reconstructed radiographs (DRRs) with artificially added shifts in the tumor location—to simulate cine EPID images with different tumor locations. Principal component analysis (PCA) was used to reduce the dimensionality of the training samples and cine EPID images acquired during the treatment. The proposed treatment verification algorithm was tested on five hypofractionated lung patients in a retrospective fashion. On average, our proposed algorithm achieved a 98.0% classification accuracy, a 97.6% recall rate and a 99.7% precision rate. This work was first presented at the Seventh International Conference on Machine Learning and Applications, San Diego, CA, USA, 11-13 December 2008.

TH-E-BRF-02: 4D-CT Ventilation Image-Based IMRT Plans Are Dosimetrically Comparable to SPECT Ventilation Image-Based Plans

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

Kida, S; University of Tokyo Hospital, Bunkyo, Tokyo; Bal, M

image-based plans, providing evidence to use 4D-CT ventilation imaging for clinical applications. Supported in part by Free to Breathe Young Investigator Research Grant and NIH/NCI R01 CA 093626. The authors thank Philips Radiation Oncology Systems for the Pinnacle3 treatment planning systems.« less

Image-based multichannel vaginal cylinder brachytherapy for the definitive treatment of gynecologic malignancies in the vagina.

PubMed

Gebhardt, Brian J; Vargo, John A; Kim, Hayeon; Houser, Christopher J; Glaser, Scott M; Sukumvanich, Paniti; Olawaiye, Alexander B; Kelley, Joseph L; Edwards, Robert P; Comerci, John T; Courtney-Brooks, Madeleine; Beriwal, Sushil

2018-06-18

Brachytherapy is integral to vaginal cancer treatment and is typically delivered using an intracavitary single-channel vaginal cylinder (SCVC) or an interstitial brachytherapy (ISBT) applicator. Multi-channel vaginal cylinder (MCVC) applicators allow for improved organ-at-risk (OAR) sparing compared to SCVC while maintaining target coverage. We present clinical outcomes of patients treated with image-based high dose-rate (HDR) brachytherapy using a MCVC. Sixty patients with vaginal cancer (27% primary vaginal and 73% recurrence from other primaries) were treated with combination external beam radiotherapy (EBRT) and image-based HDR brachytherapy utilizing a MCVC if residual disease thickness was 7 mm or less after EBRT. All pts received 3D image-based BT to a total equivalent dose of 70-80 Gy. The median high-risk clinical target volume was 24.4 cm 3 (interquartile range [IQR], 14.1), with a median dose to 90% of 77.2 Gy (IQR, 2.8). After a median follow-up of 45 months (range, 11-78), the 4-year local-regional control, distant control, DFS, and OS rates were 92.6%, 76.1%, 64.0%, and 67.2%, respectively. The 4-year LRC rates were similar between the primary vaginal (92%) and recurrent (93%) groups (p = 0.290). Pts with lymph node positive disease had a lower rate of distant control at 4 years (22.7% vs. 89.0%, p < 0.001). There were no Grade 3 or higher acute complications. The 4-year rate of late Grade 3 or higher toxicity was 2.7%. Clinical outcomes of pts with primary and recurrent vaginal cancer treated definitively in a systematic manner with combination EBRT with image-guided HDR BT utilizing a MCVC applicator demonstrate high rates of local control and low rates of severe morbidity. The MCVC technique allows interstitial implantation to be avoided in select pts with ≤7 mm residual disease thickness following EBRT while maintaining excellent clinical outcomes with extended 4-year follow-up in this rare malignancy. Copyright © 2018

Novel medical imaging technologies for disease diagnosis and treatment

NASA Astrophysics Data System (ADS)

Olego, Diego

2009-03-01

New clinical approaches for disease diagnosis, treatment and monitoring will rely on the ability of simultaneously obtaining anatomical, functional and biological information. Medical imaging technologies in combination with targeted contrast agents play a key role in delivering with ever increasing temporal and spatial resolution structural and functional information about conditions and pathologies in cardiology, oncology and neurology fields among others. This presentation will review the clinical motivations and physics challenges in on-going developments of new medical imaging techniques and the associated contrast agents. Examples to be discussed are: *The enrichment of computer tomography with spectral sensitivity for the diagnosis of vulnerable sclerotic plaque. *Time of flight positron emission tomography for improved resolution in metabolic characterization of pathologies. *Magnetic particle imaging -a novel imaging modality based on in-vivo measurement of the local concentration of iron oxide nano-particles - for blood perfusion measurement with better sensitivity, spatial resolution and 3D real time acquisition. *Focused ultrasound for therapy delivery.

Investigation of contrast-enhanced subtracted breast CT images with MAP-EM based on projection-based weighting imaging.

PubMed

Zhou, Zhengdong; Guan, Shaolin; Xin, Runchao; Li, Jianbo

2018-06-01

Contrast-enhanced subtracted breast computer tomography (CESBCT) images acquired using energy-resolved photon counting detector can be helpful to enhance the visibility of breast tumors. In such technology, one challenge is the limited number of photons in each energy bin, thereby possibly leading to high noise in separate images from each energy bin, the projection-based weighted image, and the subtracted image. In conventional low-dose CT imaging, iterative image reconstruction provides a superior signal-to-noise compared with the filtered back projection (FBP) algorithm. In this paper, maximum a posteriori expectation maximization (MAP-EM) based on projection-based weighting imaging for reconstruction of CESBCT images acquired using an energy-resolving photon counting detector is proposed, and its performance was investigated in terms of contrast-to-noise ratio (CNR). The simulation study shows that MAP-EM based on projection-based weighting imaging can improve the CNR in CESBCT images by 117.7%-121.2% compared with FBP based on projection-based weighting imaging method. When compared with the energy-integrating imaging that uses the MAP-EM algorithm, projection-based weighting imaging that uses the MAP-EM algorithm can improve the CNR of CESBCT images by 10.5%-13.3%. In conclusion, MAP-EM based on projection-based weighting imaging shows significant improvement the CNR of the CESBCT image compared with FBP based on projection-based weighting imaging, and MAP-EM based on projection-based weighting imaging outperforms MAP-EM based on energy-integrating imaging for CESBCT imaging.

Medical image security using modified chaos-based cryptography approach

NASA Astrophysics Data System (ADS)

Talib Gatta, Methaq; Al-latief, Shahad Thamear Abd

2018-05-01

The progressive development in telecommunication and networking technologies have led to the increased popularity of telemedicine usage which involve storage and transfer of medical images and related information so security concern is emerged. This paper presents a method to provide the security to the medical images since its play a major role in people healthcare organizations. The main idea in this work based on the chaotic sequence in order to provide efficient encryption method that allows reconstructing the original image from the encrypted image with high quality and minimum distortion in its content and doesn’t effect in human treatment and diagnosing. Experimental results prove the efficiency of the proposed method using some of statistical measures and robust correlation between original image and decrypted image.

WE-AB-202-11: Radiobiological Modeling of Tumor Response During Radiotherapy Based On Pre-Treatment Dynamic PET Imaging Data

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

Crispin-Ortuzar, M; Grkovski, M; Beattie, B

Purpose: To evaluate the ability of a multiscale radiobiological model of tumor response to predict mid-treatment hypoxia images, based on pretreatment imaging of perfusion and hypoxia with [18-F]FMISO dynamic PET and glucose metabolism with [18-F]FDG PET. Methods: A mechanistic tumor control probability (TCP) radiobiological model describing the interplay between tumor cell proliferation and hypoxia (Jeong et al., PMB 2013) was extended to account for intra-tumor nutrient heterogeneity, dynamic cell migration due to nutrient gradients, and stromal cells. This extended model was tested on 10 head and neck cancer patients treated with chemoradiotherapy, randomly drawn from a larger MSKCC protocol involvingmore » baseline and mid-therapy dynamic PET scans. For each voxel, initial fractions of proliferative and hypoxic tumor cells were obtained by finding an approximate solution to a system of linear equations relating cell fractions to voxel-level FDG uptake, perfusion (FMISO K{sub 1}) and hypoxia (FMISO k{sub 3}). The TCP model then predicted their evolution over time up until the mid treatment scan. Finally, the linear model was reapplied to predict each lesion’s median hypoxia level (k{sub 3}[med,sim]) which in turn was compared to the FMISO k{sub 3}[med] measured at mid-therapy. Results: The average k3[med] of the tumors in pre-treatment scans was 0.0035 min{sup −1}, with an inter-tumor standard deviation of σ[pre]=0.0034 min{sup −1}. The initial simulated k{sub 3}[med,sim] of each tumor agreed with the corresponding measurements within 0.1σ[pre]. In 7 out of 10 lesions, the mid-treatment k{sub 3}[med,sim] prediction agreed with the data within 0.3σ[pre]. The remaining cases corresponded to the most extreme relative changes in k{sub 3}[med]. Conclusion: This work presents a method to personalize the prediction of a TCP model using pre-treatment kinetic imaging data, and validates the modeling of radiotherapy response by predicting changes in median

Fully wireless pressure sensor based on endoscopy images

NASA Astrophysics Data System (ADS)

Maeda, Yusaku; Mori, Hirohito; Nakagawa, Tomoaki; Takao, Hidekuni

2018-04-01

In this paper, the result of developing a fully wireless pressure sensor based on endoscopy images for an endoscopic surgery is reported for the first time. The sensor device has structural color with a nm-scale narrow gap, and the gap is changed by air pressure. The structural color of the sensor is acquired from camera images. Pressure detection can be realized with existing endoscope configurations only. The inner air pressure of the human body should be measured under flexible-endoscope operation using the sensor. Air pressure monitoring, has two important purposes. The first is to quantitatively measure tumor size under a constant air pressure for treatment selection. The second purpose is to prevent the endangerment of a patient due to over transmission of air. The developed sensor was evaluated, and the detection principle based on only endoscopy images has been successfully demonstrated.

Current Advances in Polymer-Based Nanotheranostics for Cancer Treatment and Diagnosis

PubMed Central

2015-01-01

Nanotheranostics is a relatively new, fast-growing field that combines the advantages of treatment and diagnosis via a single nanoscale carrier. The ability to bundle both therapeutic and diagnostic capabilities into one package offers exciting prospects for the development of novel nanomedicine. Nanotheranostics can deliver treatment while simultaneously monitoring therapy response in real-time, thereby decreasing the potential of over- or under-dosing patients. Polymer-based nanomaterials, in particular, have been used extensively as carriers for both therapeutic and bioimaging agents and thus hold great promise for the construction of multifunctional theranostic formulations. Herein, we review recent advances in polymer-based systems for nanotheranostics, with a particular focus on their applications in cancer research. We summarize the use of polymer nanomaterials for drug delivery, gene delivery, and photodynamic therapy, combined with imaging agents for magnetic resonance imaging, radionuclide imaging, and fluorescence imaging. PMID:25014486

Imaging tools to measure treatment response in gout.

PubMed

Dalbeth, Nicola; Doyle, Anthony J

2018-01-01

Imaging tests are in clinical use for diagnosis, assessment of disease severity and as a marker of treatment response in people with gout. Various imaging tests have differing properties for assessing the three key disease domains in gout: urate deposition (including tophus burden), joint inflammation and structural joint damage. Dual-energy CT allows measurement of urate deposition and bone damage, and ultrasonography allows assessment of all three domains. Scoring systems have been described that allow radiological quantification of disease severity and these scoring systems may play a role in assessing the response to treatment in gout. This article reviews the properties of imaging tests, describes the available scoring systems for quantification of disease severity and discusses the challenges and controversies regarding the use of imaging tools to measure treatment response in gout. © The Author 2018. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Elastic registration of prostate MR images based on state estimation of dynamical systems

NASA Astrophysics Data System (ADS)

Marami, Bahram; Ghoul, Suha; Sirouspour, Shahin; Capson, David W.; Davidson, Sean R. H.; Trachtenberg, John; Fenster, Aaron

2014-03-01

Magnetic resonance imaging (MRI) is being increasingly used for image-guided biopsy and focal therapy of prostate cancer. A combined rigid and deformable registration technique is proposed to register pre-treatment diagnostic 3T magnetic resonance (MR) images, with the identified target tumor(s), to the intra-treatment 1.5T MR images. The pre-treatment 3T images are acquired with patients in strictly supine position using an endorectal coil, while 1.5T images are obtained intra-operatively just before insertion of the ablation needle with patients in the lithotomy position. An intensity-based registration routine rigidly aligns two images in which the transformation parameters is initialized using three pairs of manually selected approximate corresponding points. The rigid registration is followed by a deformable registration algorithm employing a generic dynamic linear elastic deformation model discretized by the finite element method (FEM). The model is used in a classical state estimation framework to estimate the deformation of the prostate based on a similarity metric between pre- and intra-treatment images. Registration results using 10 sets of prostate MR images showed that the proposed method can significantly improve registration accuracy in terms of target registration error (TRE) for all prostate substructures. The root mean square (RMS) TRE of 46 manually identified fiducial points was found to be 2.40+/-1.20 mm, 2.51+/-1.20 mm, and 2.28+/-1.22mm for the whole gland (WG), central gland (CG), and peripheral zone (PZ), respectively after deformable registration. These values are improved from 3.15+/-1.60 mm, 3.09+/-1.50 mm, and 3.20+/-1.73mm in the WG, CG and PZ, respectively resulted from rigid registration. Registration results are also evaluated based on the Dice similarity coefficient (DSC), mean absolute surface distances (MAD) and maximum absolute surface distances (MAXD) of the WG and CG in the prostate images.

International inter-rater agreement in scoring acne severity utilizing cloud-based image sharing of mobile phone photographs.

PubMed

Foolad, Negar; Ornelas, Jennifer N; Clark, Ashley K; Ali, Ifrah; Sharon, Victoria R; Al Mubarak, Luluah; Lopez, Andrés; Alikhan, Ali; Al Dabagh, Bishr; Firooz, Alireza; Awasthi, Smita; Liu, Yu; Li, Chin-Shang; Sivamani, Raja K

2017-09-01

Cloud-based image sharing technology allows facilitated sharing of images. Cloud-based image sharing technology has not been well-studied for acne assessments or treatment preferences, among international evaluators. We evaluated inter-rater variability of acne grading and treatment recommendations among an international group of dermatologists that assessed photographs. This is a prospective, single visit photographic study to assess inter-rater agreement of acne photographs shared through an integrated mobile device, cloud-based, and HIPAA-compliant platform. Inter-rater agreements for global acne assessment and acne lesion counts were evaluated by the Kendall's coefficient of concordance while correlations between treatment recommendations and acne severity were calculated by Spearman's rank correlation coefficient. There was good agreement for the evaluation of inflammatory lesions (KCC = 0.62, P < 0.0001), noninflammatory lesions (KCC = 0.62, P < 0.0001), and the global acne grading system score (KCC = 0.69, P < 0.0001). Topical retinoid, oral antibiotic, and isotretinoin treatment preferences correlated with photographic based acne severity. Our study supports the use of mobile phone based photography and cloud-based image sharing for acne assessment. Cloud-based sharing may facilitate acne care and research among international collaborators. © 2017 The International Society of Dermatology.

[Effect of body image in adolescent orthodontic treatment].

PubMed

Minghui, Peng; Jing, Kang; Xiao, Deng

2017-10-01

This study was designed to probe the psychological factors adolescent orthodontic patients, the role of body image and self-esteem in the whole process of orthodontic treatment and the impact on the efficacy and satisfaction of orthodontic. Five hundred and twenty-eight patients were selected in this study. The Aesthetic Component of the Index of Orthodontic Treatment Need (IOTN-AC) , Rosenberg Self-Esteem Scale (SES), Negative Physical Self-General (NPS-G) and other body analysis scale study after orthodontic lasted 18-24 months were used to investigate the role of body image in adolescent orthodontic treatment. Esthetic evaluation of patients teeth after correction had been significantly improved, patient self-evaluation difference IOTN-AC doctor evaluation, Psychosocial Impact of Dental Aesthetics Questionnaire-tooth confidence, aesthetic concerns, psychological impact and social function were significantly improved. The improvement of the dental aesthetics component (T2 when doctors evaluate IOTN-AC) was positively correlated with the evaluation of the efficacy, and was significantly negatively correlated with the negative emotions of patients at baseline. Negative body image-dental dissatisfied-cognitive component and the affective component, the overall negative body image and negative emotions can predict patient satisfaction with treatment efficacy. Orthodontic treatment not only improves the self-aesthetic evaluation of adolescent patients, but also has a positive effect on the mental health of adolescent patients.

Imaging Feedback of Histotripsy Treatments Using Ultrasound Shear Wave Elastography

PubMed Central

Wang, Tzu-Yin; Hall, Timothy L.; Xu, Zhen; Fowlkes, J. Brian; Cain, Charles A.

2013-01-01

Histotripsy is a cavitation-based ultrasound therapy that mechanically fractionates soft solid tissues into fluid-like homogenates. This paper investigates the feasibility of imaging the tissue elasticity change during the histotripsy process as a tool to provide feedback for the treatments. The treatments were performed on agar tissue phantoms and ex vivo kidneys using 3-cycle ultrasound pulses delivered by a 750-kHz therapeutic array at peak negative/positive pressure of 17/108 MPa and a repetition rate of 50 Hz. Lesions with different degrees of damage were created with increasing numbers of therapy pulses from 0 to 2000 pulses per treatment location. The elasticity of the lesions was measured with ultrasound shear wave elastography, in which a quasi-planar shear wave was induced by acoustic radiation force generated by the therapeutic array, and tracked with ultrasound imaging at 3000 frames per second. Based on the shear wave velocity calculated from the sequentially captured frames, the Young’s modulus was reconstructed. Results showed that the lesions were more easily identified on the shear wave velocity images than on B-mode images. As the number of therapy pulses increased from 0 to 2000 pulses/location, the Young’s modulus decreased exponentially from 22.1 ± 2.7 to 2.1 ± 1.1 kPa in the tissue phantoms (R2 = 0.99, N = 9 each), and from 33.0 ± 7.1 to 4.0 ± 2.5 kPa in the ex vivo kidneys (R2 = 0.99, N = 8 each). Correspondingly, the tissues transformed from completely intact to completely fractionated as examined via histology. A good correlation existed between the lesions’ Young’s modulus and the degree of tissue fractionation as examined with the percentage of remaining structurally intact cell nuclei (R2 = 0.91, N = 8 each). These results indicate that lesions produced by histotripsy can be detected with high sensitivity using shear wave elastography. Because the decrease in the tissue elasticity corresponded well with the morphological and

Imaging feedback of histotripsy treatments using ultrasound shear wave elastography.

PubMed

Wang, Tzu-Yin; Hall, Timothy L; Xu, Zhen; Fowlkes, J Brian; Cain, Charles A

2012-06-01

Histotripsy is a cavitation-based ultrasound therapy that mechanically fractionates soft solid tissues into fluid-like homogenates. This paper investigates the feasibility of imaging the tissue elasticity change during the histotripsy process as a tool to provide feedback for the treatments. The treatments were performed on agar tissue phantoms and ex vivo kidneys using 3-cycle ultrasound pulses delivered by a 750-kHz therapeutic array at peak negative/positive pressure of 17/108 MPa and a repetition rate of 50 Hz. Lesions with different degrees of damage were created with increasing numbers of therapy pulses from 0 to 2000 pulses per treatment location. The elasticity of the lesions was measured with ultrasound shear wave elastography, in which a quasi-planar shear wave was induced by acoustic radiation force generated by the therapeutic array, and tracked with ultrasound imaging at 3000 frames per second. Based on the shear wave velocity calculated from the sequentially captured frames, the Young's modulus was reconstructed. Results showed that the lesions were more easily identified on the shear wave velocity images than on B-mode images. As the number of therapy pulses increased from 0 to 2000 pulses/location, the Young's modulus decreased exponentially from 22.1 ± 2.7 to 2.1 ± 1.1 kPa in the tissue phantoms (R2 = 0.99, N = 9 each), and from 33.0 ± 7.1 to 4.0 ± 2.5 kPa in the ex vivo kidneys (R2 = 0.99, N = 8 each). Correspondingly, the tissues transformed from completely intact to completely fractionated as examined via histology. A good correlation existed between the lesions' Young's modulus and the degree of tissue fractionation as examined with the percentage of remaining structurally intact cell nuclei (R2 = 0.91, N = 8 each). These results indicate that lesions produced by histotripsy can be detected with high sensitivity using shear wave elastography. Because the decrease in the tissue elasticity corresponded well with the morphological and

Nanomaterials in Neural-Stem-Cell-Mediated Regenerative Medicine: Imaging and Treatment of Neurological Diseases.

PubMed

Zhang, Bingbo; Yan, Wei; Zhu, Yanjing; Yang, Weitao; Le, Wenjun; Chen, Bingdi; Zhu, Rongrong; Cheng, Liming

2018-04-01

Patients are increasingly being diagnosed with neuropathic diseases, but are rarely cured because of the loss of neurons in damaged tissues. This situation creates an urgent clinical need to develop alternative treatment strategies for effective repair and regeneration of injured or diseased tissues. Neural stem cells (NSCs), highly pluripotent cells with the ability of self-renewal and potential for multidirectional differentiation, provide a promising solution to meet this demand. However, some serious challenges remaining to be addressed are the regulation of implanted NSCs, tracking their fate, monitoring their interaction with and responsiveness to the tissue environment, and evaluating their treatment efficacy. Nanomaterials have been envisioned as innovative components to further empower the field of NSC-based regenerative medicine, because their unique physicochemical characteristics provide unparalleled solutions to the imaging and treatment of diseases. By building on the advantages of nanomaterials, tremendous efforts have been devoted to facilitate research into the clinical translation of NSC-based therapy. Here, recent work on emerging nanomaterials is highlighted and their performance in the imaging and treatment of neurological diseases is evaluated, comparing the strengths and weaknesses of various imaging modalities currently used. The underlying mechanisms of therapeutic efficacy are discussed, and future research directions are suggested. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Advances in Magnetic Resonance Imaging of the Skull Base

PubMed Central

Kirsch, Claudia F.E.

2014-01-01

Introduction Over the past 20 years, magnetic resonance imaging (MRI) has advanced due to new techniques involving increased magnetic field strength and developments in coils and pulse sequences. These advances allow increased opportunity to delineate the complex skull base anatomy and may guide the diagnosis and treatment of the myriad of pathologies that can affect the skull base. Objectives The objective of this article is to provide a brief background of the development of MRI and illustrate advances in skull base imaging, including techniques that allow improved conspicuity, characterization, and correlative physiologic assessment of skull base pathologies. Data Synthesis Specific radiographic illustrations of increased skull base conspicuity including the lower cranial nerves, vessels, foramina, cerebrospinal fluid (CSF) leaks, and effacement of endolymph are provided. In addition, MRIs demonstrating characterization of skull base lesions, such as recurrent cholesteatoma versus granulation tissue or abscess versus tumor, are also provided as well as correlative clinical findings in CSF flow studies in a patient pre- and post-suboccipital decompression for a Chiari I malformation. Conclusions This article illustrates MRI radiographic advances over the past 20 years, which have improved clinicians' ability to diagnose, define, and hopefully improve the treatment and outcomes of patients with underlying skull base pathologies. PMID:25992137

Predicting Treatment Response in Social Anxiety Disorder From Functional Magnetic Resonance Imaging

PubMed Central

Doehrmann, Oliver; Ghosh, Satrajit S.; Polli, Frida E.; Reynolds, Gretchen O.; Horn, Franziska; Keshavan, Anisha; Triantafyllou, Christina; Saygin, Zeynep M.; Whitfield-Gabrieli, Susan; Hofmann, Stefan G.; Pollack, Mark; Gabrieli, John D.

2013-01-01

Context Current behavioral measures poorly predict treatment outcome in social anxiety disorder (SAD). To our knowledge, this is the first study to examine neuroimaging-based treatment prediction in SAD. Objective To measure brain activation in patients with SAD as a biomarker to predict subsequent response to cognitive behavioral therapy (CBT). Design Functional magnetic resonance imaging (fMRI) data were collected prior to CBT intervention. Changes in clinical status were regressed on brain responses and tested for selectivity for social stimuli. Setting Patients were treated with protocol-based CBT at anxiety disorder programs at Boston University or Massachusetts General Hospital and underwent neuroimaging data collection at Massachusetts Institute of Technology. Patients Thirty-nine medication-free patients meeting DSM-IV criteria for the generalized subtype of SAD. Interventions Brain responses to angry vs neutral faces or emotional vs neutral scenes were examined with fMRI prior to initiation of CBT. Main Outcome Measures Whole-brain regression analyses with differential fMRI responses for angry vs neutral faces and changes in Liebowitz Social Anxiety Scale score as the treatment outcome measure. Results Pretreatment responses significantly predicted subsequent treatment outcome of patients selectively for social stimuli and particularly in regions of higher-order visual cortex. Combining the brain measures with information on clinical severity accounted for more than 40% of the variance in treatment response and substantially exceeded predictions based on clinical measures at baseline. Prediction success was unaffected by testing for potential confounding factors such as depression severity at baseline. Conclusions The results suggest that brain imaging can provide biomarkers that substantially improve predictions for the success of cognitive behavioral interventions and more generally suggest that such biomarkers may offer evidence-based, personalized

Single image interpolation via adaptive nonlocal sparsity-based modeling.

PubMed

Romano, Yaniv; Protter, Matan; Elad, Michael

2014-07-01

Single image interpolation is a central and extensively studied problem in image processing. A common approach toward the treatment of this problem in recent years is to divide the given image into overlapping patches and process each of them based on a model for natural image patches. Adaptive sparse representation modeling is one such promising image prior, which has been shown to be powerful in filling-in missing pixels in an image. Another force that such algorithms may use is the self-similarity that exists within natural images. Processing groups of related patches together exploits their correspondence, leading often times to improved results. In this paper, we propose a novel image interpolation method, which combines these two forces-nonlocal self-similarities and sparse representation modeling. The proposed method is contrasted with competitive and related algorithms, and demonstrated to achieve state-of-the-art results.

Body Image of Women Submitted to Breast Cancer Treatment

PubMed

Guedes, Thais Sousa Rodrigues; Dantas de Oliveira, Nayara Priscila; Holanda, Ayrton Martins; Reis, Mariane Albuquerque; Silva, Clécia Patrocínio da; Rocha e Silva, Bárbara Layse; Cancela, Marianna de Camargo; de Souza, Dyego Leandro Bezerra

2018-06-25

Background: The study of body image includes the perception of women regarding the physical appearance of their own body. The objective of the present study was to verify the prevalence of body image dissatisfaction and its associated factors in women submitted to breast cancer treatment. Methods: A cross-sectional study carried out with 103 female residents of the municipality of Natal (Northeast Brazil), diagnosed with breast cancer who had undergone cancer treatment for at least 12 months prior to the study, and remained under clinical monitoring. The variable body image was measured through the validated Body Image Scale (BIS). Socioeconomic variables and clinical history were also collected through an individual interview with each participant. The Pearson’s chi-squared test (Fisher’s Exact) was utilized for bivariate analysis, calculating the prevalence ratio with 95% confidence interval. Poisson regression with robust variance was utilized for multivariate analysis. The statistical significance considered was 0.05. Results: The prevalence of body image dissatisfaction was 74.8% CI (65%-82%). Statistically significant associations were observed between body image and multi-professional follow-up (p=0.009) and return to employment after treatment (p=0.022). Conclusion: It was concluded that women who reported employment after cancer treatment presented more alterations in self-perception concerning their appearance. Patients who did not receive multi-professional follow-up reported negative body image, evidencing the need for strategies that increase and improve healthcare, aiming to meet the demands of this population. Creative Commons Attribution License

SU-F-J-54: Towards Real-Time Volumetric Imaging Using the Treatment Beam and KV Beam

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

Chen, M; Rozario, T; Liu, A

Purpose: Existing real-time imaging uses dual (orthogonal) kV beam fluoroscopies and may result in significant amount of extra radiation to patients, especially for prolonged treatment cases. In addition, kV projections only provide 2D information, which is insufficient for in vivo dose reconstruction. We propose real-time volumetric imaging using prior knowledge of pre-treatment 4D images and real-time 2D transit data of treatment beam and kV beam. Methods: The pre-treatment multi-snapshot volumetric images are used to simulate 2D projections of both the treatment beam and kV beam, respectively, for each treatment field defined by the control point. During radiation delivery, the transitmore » signals acquired by the electronic portal image device (EPID) are processed for every projection and compared with pre-calculation by cross-correlation for phase matching and thus 3D snapshot identification or real-time volumetric imaging. The data processing involves taking logarithmic ratios of EPID signals with respect to the air scan to reduce modeling uncertainties in head scatter fluence and EPID response. Simulated 2D projections are also used to pre-calculate confidence levels in phase matching. Treatment beam projections that have a low confidence level either in pre-calculation or real-time acquisition will trigger kV beams so that complementary information can be exploited. In case both the treatment beam and kV beam return low confidence in phase matching, a predicted phase based on linear regression will be generated. Results: Simulation studies indicated treatment beams provide sufficient confidence in phase matching for most cases. At times of low confidence from treatment beams, kV imaging provides sufficient confidence in phase matching due to its complementary configuration. Conclusion: The proposed real-time volumetric imaging utilizes the treatment beam and triggers kV beams for complementary information when the treatment beam along does not provide

Smartphone-based multispectral imaging: system development and potential for mobile skin diagnosis

PubMed Central

Kim, Sewoong; Cho, Dongrae; Kim, Jihun; Kim, Manjae; Youn, Sangyeon; Jang, Jae Eun; Je, Minkyu; Lee, Dong Hun; Lee, Boreom; Farkas, Daniel L.; Hwang, Jae Youn

2016-01-01

We investigate the potential of mobile smartphone-based multispectral imaging for the quantitative diagnosis and management of skin lesions. Recently, various mobile devices such as a smartphone have emerged as healthcare tools. They have been applied for the early diagnosis of nonmalignant and malignant skin diseases. Particularly, when they are combined with an advanced optical imaging technique such as multispectral imaging and analysis, it would be beneficial for the early diagnosis of such skin diseases and for further quantitative prognosis monitoring after treatment at home. Thus, we demonstrate here the development of a smartphone-based multispectral imaging system with high portability and its potential for mobile skin diagnosis. The results suggest that smartphone-based multispectral imaging and analysis has great potential as a healthcare tool for quantitative mobile skin diagnosis. PMID:28018743

Smartphone-based multispectral imaging: system development and potential for mobile skin diagnosis.

PubMed

Kim, Sewoong; Cho, Dongrae; Kim, Jihun; Kim, Manjae; Youn, Sangyeon; Jang, Jae Eun; Je, Minkyu; Lee, Dong Hun; Lee, Boreom; Farkas, Daniel L; Hwang, Jae Youn

2016-12-01

We investigate the potential of mobile smartphone-based multispectral imaging for the quantitative diagnosis and management of skin lesions. Recently, various mobile devices such as a smartphone have emerged as healthcare tools. They have been applied for the early diagnosis of nonmalignant and malignant skin diseases. Particularly, when they are combined with an advanced optical imaging technique such as multispectral imaging and analysis, it would be beneficial for the early diagnosis of such skin diseases and for further quantitative prognosis monitoring after treatment at home. Thus, we demonstrate here the development of a smartphone-based multispectral imaging system with high portability and its potential for mobile skin diagnosis. The results suggest that smartphone-based multispectral imaging and analysis has great potential as a healthcare tool for quantitative mobile skin diagnosis.

Quality Improvement Guidelines for Imaging Detection and Treatment of Endoleaks following Endovascular Aneurysm Repair (EVAR)

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

Rand, T., E-mail: Thomas.Rand@wienkav.at; Uberoi, R.; Cil, B.

2013-02-15

Major concerns after aortic aneurysm repair are caused by the presence of endoleaks, which are defined as persistent perigraft flow within the aortic aneurysm sac. Diagnosis of endoleaks can be performed with various imaging modalities, and indications for treatment are based on further subclassifications. Early detection and correct classification of endoleaks are crucial for planning patient management. The vast majority of endoleaks can be treated successfully by interventional means. Guidelines for Imaging Detection and Treatment of endoleaks are described in this article.

RayPlus: a Web-Based Platform for Medical Image Processing.

PubMed

Yuan, Rong; Luo, Ming; Sun, Zhi; Shi, Shuyue; Xiao, Peng; Xie, Qingguo

2017-04-01

Medical image can provide valuable information for preclinical research, clinical diagnosis, and treatment. As the widespread use of digital medical imaging, many researchers are currently developing medical image processing algorithms and systems in order to accommodate a better result to clinical community, including accurate clinical parameters or processed images from the original images. In this paper, we propose a web-based platform to present and process medical images. By using Internet and novel database technologies, authorized users can easily access to medical images and facilitate their workflows of processing with server-side powerful computing performance without any installation. We implement a series of algorithms of image processing and visualization in the initial version of Rayplus. Integration of our system allows much flexibility and convenience for both research and clinical communities.

SU-F-J-178: A Computer Simulation Model Observer for Task-Based Image Quality Assessment in Radiation Therapy

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

Dolly, S; Mutic, S; Anastasio, M

Purpose: Traditionally, image quality in radiation therapy is assessed subjectively or by utilizing physically-based metrics. Some model observers exist for task-based medical image quality assessment, but almost exclusively for diagnostic imaging tasks. As opposed to disease diagnosis, the task for image observers in radiation therapy is to utilize the available images to design and deliver a radiation dose which maximizes patient disease control while minimizing normal tissue damage. The purpose of this study was to design and implement a new computer simulation model observer to enable task-based image quality assessment in radiation therapy. Methods: A modular computer simulation framework wasmore » developed to resemble the radiotherapy observer by simulating an end-to-end radiation therapy treatment. Given images and the ground-truth organ boundaries from a numerical phantom as inputs, the framework simulates an external beam radiation therapy treatment and quantifies patient treatment outcomes using the previously defined therapeutic operating characteristic (TOC) curve. As a preliminary demonstration, TOC curves were calculated for various CT acquisition and reconstruction parameters, with the goal of assessing and optimizing simulation CT image quality for radiation therapy. Sources of randomness and bias within the system were analyzed. Results: The relationship between CT imaging dose and patient treatment outcome was objectively quantified in terms of a singular value, the area under the TOC (AUTOC) curve. The AUTOC decreases more rapidly for low-dose imaging protocols. AUTOC variation introduced by the dose optimization algorithm was approximately 0.02%, at the 95% confidence interval. Conclusion: A model observer has been developed and implemented to assess image quality based on radiation therapy treatment efficacy. It enables objective determination of appropriate imaging parameter values (e.g. imaging dose). Framework flexibility allows for

Enhance wound healing monitoring through a thermal imaging based smartphone app

NASA Astrophysics Data System (ADS)

Yi, Steven; Lu, Minta; Yee, Adam; Harmon, John; Meng, Frank; Hinduja, Saurabh

2018-03-01

In this paper, we present a thermal imaging based app to augment traditional appearance based wound growth monitoring. Accurate diagnose and track of wound healing enables physicians to effectively assess, document, and individualize the treatment plan given to each wound patient. Currently, wounds are primarily examined by physicians through visual appearance and wound area. However, visual information alone cannot present a complete picture on a wound's condition. In this paper, we use a smartphone attached thermal imager and evaluate its effectiveness on augmenting visual appearance based wound diagnosis. Instead of only monitoring wound temperature changes on a wound, our app presents physicians a comprehensive measurements including relative temperature, wound healing thermal index, and wound blood flow. Through the rat wound experiments and by monitoring the integrated thermal measurements over 3 weeks of time frame, our app is able to show the underlying healing process through the blood flow. The implied significance of our app design and experiment includes: (a) It is possible to use a low cost smartphone attached thermal imager for added value on wound assessment, tracking, and treatment; and (b) Thermal mobile app can be used for remote wound healing assessment for mobile health based solution.

Granulomatous lobular mastitis: imaging, diagnosis, and treatment.

PubMed

Hovanessian Larsen, Linda J; Peyvandi, Banafsheh; Klipfel, Nancy; Grant, Edward; Iyengar, Geeta

2009-08-01

Granulomatous lobular mastitis is a rare chronic inflammatory disease that has clinical and radiologic findings similar to those of breast cancer. We performed a retrospective analysis of clinical, imaging, and treatment findings in 54 women diagnosed with granulomatous lobular mastitis between January 2000 and April 2008. The imaging findings of granulomatous lobular mastitis overlap with those of malignancy. The most common presentation is a focal asymmetric density on mammography and an irregular hypoechoic mass with tubular extensions on ultrasound. Core biopsy is typically diagnostic. Once the diagnosis is established by tissue sampling, corticosteroids are the first line of treatment.

MR-OPERA: A Multicenter/Multivendor Validation of Magnetic Resonance Imaging-Only Prostate Treatment Planning Using Synthetic Computed Tomography Images.

PubMed

Persson, Emilia; Gustafsson, Christian; Nordström, Fredrik; Sohlin, Maja; Gunnlaugsson, Adalsteinn; Petruson, Karin; Rintelä, Niina; Hed, Kristoffer; Blomqvist, Lennart; Zackrisson, Björn; Nyholm, Tufve; Olsson, Lars E; Siversson, Carl; Jonsson, Joakim

2017-11-01

To validate the dosimetric accuracy and clinical robustness of a commercially available software for magnetic resonance (MR) to synthetic computed tomography (sCT) conversion, in an MR imaging-only workflow for 170 prostate cancer patients. The 4 participating centers had MriPlanner (Spectronic Medical), an atlas-based sCT generation software, installed as a cloud-based service. A T2-weighted MR sequence, covering the body contour, was added to the clinical protocol. The MR images were sent from the MR scanner workstation to the MriPlanner platform. The sCT was automatically returned to the treatment planning system. Four MR scanners and 2 magnetic field strengths were included in the study. For each patient, a CT-treatment plan was created and approved according to clinical practice. The sCT was rigidly registered to the CT, and the clinical treatment plan was recalculated on the sCT. The dose distributions from the CT plan and the sCT plan were compared according to a set of dose-volume histogram parameters and gamma evaluation. Treatment techniques included volumetric modulated arc therapy, intensity modulated radiation therapy, and conventional treatment using 2 treatment planning systems and different dose calculation algorithms. The overall (multicenter/multivendor) mean dose differences between sCT and CT dose distributions were below 0.3% for all evaluated organs and targets. Gamma evaluation showed a mean pass rate of 99.12% (0.63%, 1 SD) in the complete body volume and 99.97% (0.13%, 1 SD) in the planning target volume using a 2%/2-mm global gamma criteria. Results of the study show that the sCT conversion method can be used clinically, with minimal differences between sCT and CT dose distributions for target and relevant organs at risk. The small differences seen are consistent between centers, indicating that an MR imaging-only workflow using MriPlanner is robust for a variety of field strengths, vendors, and treatment techniques. Copyright © 2017 The

Development of a virtual speaking simulator using Image Based Rendering.

PubMed

Lee, J M; Kim, H; Oh, M J; Ku, J H; Jang, D P; Kim, I Y; Kim, S I

2002-01-01

The fear of speaking is often cited as the world's most common social phobia. The rapid growth of computer technology has enabled the use of virtual reality (VR) for the treatment of the fear of public speaking. There are two techniques for building virtual environments for the treatment of this fear: a model-based and a movie-based method. Both methods have the weakness that they are unrealistic and not controllable individually. To understand these disadvantages, this paper presents a virtual environment produced with Image Based Rendering (IBR) and a chroma-key simultaneously. IBR enables the creation of realistic virtual environments where the images are stitched panoramically with the photos taken from a digital camera. And the use of chroma-keys puts virtual audience members under individual control in the environment. In addition, real time capture technique is used in constructing the virtual environments enabling spoken interaction between the subject and a therapist or another subject.

Calculation of Lung Cancer Volume of Target Based on Thorax Computed Tomography Images using Active Contour Segmentation Method for Treatment Planning System

NASA Astrophysics Data System (ADS)

Patra Yosandha, Fiet; Adi, Kusworo; Edi Widodo, Catur

2017-06-01

In this research, calculation process of the lung cancer volume of target based on computed tomography (CT) thorax images was done. Volume of the target calculation was done in purpose to treatment planning system in radiotherapy. The calculation of the target volume consists of gross tumor volume (GTV), clinical target volume (CTV), planning target volume (PTV) and organs at risk (OAR). The calculation of the target volume was done by adding the target area on each slices and then multiply the result with the slice thickness. Calculations of area using of digital image processing techniques with active contour segmentation method. This segmentation for contouring to obtain the target volume. The calculation of volume produced on each of the targets is 577.2 cm3 for GTV, 769.9 cm3 for CTV, 877.8 cm3 for PTV, 618.7 cm3 for OAR 1, 1,162 cm3 for OAR 2 right, and 1,597 cm3 for OAR 2 left. These values indicate that the image processing techniques developed can be implemented to calculate the lung cancer target volume based on CT thorax images. This research expected to help doctors and medical physicists in determining and contouring the target volume quickly and precisely.

Evidence-Based Cancer Imaging

PubMed Central

Khorasani, Ramin

2017-01-01

With the advances in the field of oncology, imaging is increasingly used in the follow-up of cancer patients, leading to concerns about over-utilization. Therefore, it has become imperative to make imaging more evidence-based, efficient, cost-effective and equitable. This review explores the strategies and tools to make diagnostic imaging more evidence-based, mainly in the context of follow-up of cancer patients. PMID:28096722

Contour-based image warping

NASA Astrophysics Data System (ADS)

Chan, Kwai H.; Lau, Rynson W.

1996-09-01

Image warping concerns about transforming an image from one spatial coordinate to another. It is widely used for the vidual effect of deforming and morphing images in the film industry. A number of warping techniques have been introduced, which are mainly based on the corresponding pair mapping of feature points, feature vectors or feature patches (mostly triangular or quadrilateral). However, very often warping of an image object with an arbitrary shape is required. This requires a warping technique which is based on boundary contour instead of feature points or feature line-vectors. In addition, when feature point or feature vector based techniques are used, approximation of the object boundary by using point or vectors is required. In this case, the matching process of the corresponding pairs will be very time consuming if a fine approximation is required. In this paper, we propose a contour-based warping technique for warping image objects with arbitrary shapes. The novel idea of the new method is the introduction of mathematical morphology to allow a more flexible control of image warping. Two morphological operators are used as contour determinators. The erosion operator is used to warp image contents which are inside a user specified contour while the dilation operation is used to warp image contents which are outside of the contour. This new method is proposed to assist further development of a semi-automatic motion morphing system when accompanied with robust feature extractors such as deformable template or active contour model.

Imaging of the central skull base.

PubMed

Borges, Alexandra

2009-08-01

The central skull base (CSB) constitutes a frontier between the extracranial head and neck and the middle cranial fossa. The anatomy of this region is complex, containing most of the bony foramina and canals of the skull base traversed by several neurovascular structures that can act as routes of spread for pathologic processes. Lesions affecting the CSB can be intrinsic to its bony-cartilaginous components; can arise from above, within the intracranial compartment; or can arise from below, within the extracranial head and neck. Crosssectional imaging is indispensable in the diagnosis, treatment planning, and follow-up of patients with CSB lesions. This review focuses on a systematic approach to this region based on an anatomic division that takes into account the major tissue constituents of the CSB.

Imaging of the central skull base.

PubMed

Borges, Alexandra

2009-11-01

The central skull base (CSB) constitutes a frontier between the extracranial head and neck and the middle cranial fossa. The anatomy of this region is complex, containing most of the bony foramina and canals of the skull base traversed by several neurovascular structures that can act as routes of spread for pathologic processes. Lesions affecting the CSB can be intrinsic to its bony-cartilaginous components; can arise from above, within the intracranial compartment; or can arise from below, within the extracranial head and neck. Crosssectional imaging is indispensable in the diagnosis, treatment planning, and follow-up of patients with CSB lesions. This review focuses on a systematic approach to this region based on an anatomic division that takes into account the major tissue constituents of the CSB.

SU-F-T-626: Intracranial SRS Re-Treatment Without Acquisition of New CT Images

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

Wiant, D; Manning, M; Liu, H

Purpose: Linear accelerator based stereotactic radiosurgery (SRS) for multiple intracranial lesions with frequent surveillance is becoming a popular treatment option. This strategy leads to retreatment with SRS as new lesions arise. Currently, each course of treatment uses magnetic resonance (MR) and computed tomography (CT) images for treatment planning. We propose that new MR images, with course 1 CT images, may be used for future treatment plans with negligible loss of dosimetric accuracy. Methods: Ten patients that received multiple courses of SRS were retrospectively reviewed. The treatment plans and contours from non-initial courses were copied to the initial CTs and recalculated.more » Doses metrics for the plans calculated on the initial CTs and later CTs were compared. All CT scans were acquired on a Philips CT scanner with a 600 mm field of view and 1 mm slice thickness (Philips Healthcare, Andover, MA). All targets were planned to 20 Gy and calculated in Eclipse V. 13.6 (Varian, Palo Alto, CA) using analytic anisotropic algorithm with 1 mm calculation grid. Results: Sixteen lesions were evaluated. The mean time between courses was 250 +/− 215 days (range 103–979). The mean target volume was 2.0 +/− 2.9 cc (range 0.1–10.1). The average difference in mean target dose between the two calculations was 0.2 +/− 0.3 Gy (range 0.0 – 1.0). The mean conformity index (CI) was 1.28 +/− 0.14 (range 1.07 – 1.82). The average difference in CI was 0.03 +/− 0.16 (range 0.00 – 0.44). Targets volumes < 0.5 cc showed the largest changes in both metrics. Conclusion: Continued treatment based on initial CT images is feasible. Dose calculation on the initial CT for future treatments provides reasonable dosimetric accuracy. Changes in dose metrics are largest for small volumes, and are likely dominated by partial volume effects in target definition.« less

Optimization of Focused Ultrasound and Image Based Modeling in Image Guided Interventions

NASA Astrophysics Data System (ADS)

Almekkawy, Mohamed Khaled Ibrahim

Image-guided high intensity focused ultrasound (HIFU) is becoming increasingly accepted as a form of noninvasive ablative therapy for the treatment of prostate cancer, uterine fibroids and other tissue abnormalities. In principle, HIFU beams can be focused within small volumes which results in forming precise lesions within the target volume (e.g. tumor, atherosclerotic plaque) while sparing the intervening tissue. With this precision, HIFU offers the promise of noninvasive tumor therapy. The goal of this thesis is to develop an image-guidance mode with an interactive image-based computational modeling of tissue response to HIFU. This model could be used in treatment planning and post-treatment retrospective evaluation of treatment outcome(s). Within the context of treatment planning, the challenge of using HIFU to target tumors in organs partially obscured by the rib cage are addressed. Ribs distort HIFU beams in a manner that reduces the focusing gain at the target (tumor) and could cause a treatment-limiting collateral damage. We present a refocusing algorithms to efficiently steer higher power towards the target while limiting power deposition on the ribs, improving the safety and efficacy of tumor ablation. Our approach is based on an approximation of a non-convex to a convex optimization known as the semidefinite relaxation (SDR) technique. An important advantage of the SDR method over previously proposed optimization methods is the explicit control of the sidelobes in the focal plane. A finite-difference time domain (FDTD) heterogeneous propagation model of a 1-MHz concave phased array was used to model the acoustic propagation and temperature simulations in different tissues including ribs. The numerical methods developed for the refocusing problem are also used for retrospective analysis of targeting of atherosclerotic plaques using HIFU. Cases were simulated where seven adjacent HIFU shots (5000 W/cm2, 2 sec exposure time) were focused at the plaque

Edge-based correlation image registration for multispectral imaging

DOEpatents

Nandy, Prabal [Albuquerque, NM

2009-11-17

Registration information for images of a common target obtained from a plurality of different spectral bands can be obtained by combining edge detection and phase correlation. The images are edge-filtered, and pairs of the edge-filtered images are then phase correlated to produce phase correlation images. The registration information can be determined based on these phase correlation images.

[Non-rigid medical image registration based on mutual information and thin-plate spline].

PubMed

Cao, Guo-gang; Luo, Li-min

2009-01-01

To get precise and complete details, the contrast in different images is needed in medical diagnosis and computer assisted treatment. The image registration is the basis of contrast, but the regular rigid registration does not satisfy the clinic requirements. A non-rigid medical image registration method based on mutual information and thin-plate spline was present. Firstly, registering two images globally based on mutual information; secondly, dividing reference image and global-registered image into blocks and registering them; then getting the thin-plate spline transformation according to the shift of blocks' center; finally, applying the transformation to the global-registered image. The results show that the method is more precise than the global rigid registration based on mutual information and it reduces the complexity of getting control points and satisfy the clinic requirements better by getting control points of the thin-plate transformation automatically.

A fully automatic approach for multimodal PET and MR image segmentation in gamma knife treatment planning.

PubMed

Rundo, Leonardo; Stefano, Alessandro; Militello, Carmelo; Russo, Giorgio; Sabini, Maria Gabriella; D'Arrigo, Corrado; Marletta, Francesco; Ippolito, Massimo; Mauri, Giancarlo; Vitabile, Salvatore; Gilardi, Maria Carla

2017-06-01

Nowadays, clinical practice in Gamma Knife treatments is generally based on MRI anatomical information alone. However, the joint use of MRI and PET images can be useful for considering both anatomical and metabolic information about the lesion to be treated. In this paper we present a co-segmentation method to integrate the segmented Biological Target Volume (BTV), using [ 11 C]-Methionine-PET (MET-PET) images, and the segmented Gross Target Volume (GTV), on the respective co-registered MR images. The resulting volume gives enhanced brain tumor information to be used in stereotactic neuro-radiosurgery treatment planning. GTV often does not match entirely with BTV, which provides metabolic information about brain lesions. For this reason, PET imaging is valuable and it could be used to provide complementary information useful for treatment planning. In this way, BTV can be used to modify GTV, enhancing Clinical Target Volume (CTV) delineation. A novel fully automatic multimodal PET/MRI segmentation method for Leksell Gamma Knife ® treatments is proposed. This approach improves and combines two computer-assisted and operator-independent single modality methods, previously developed and validated, to segment BTV and GTV from PET and MR images, respectively. In addition, the GTV is utilized to combine the superior contrast of PET images with the higher spatial resolution of MRI, obtaining a new BTV, called BTV MRI . A total of 19 brain metastatic tumors, undergone stereotactic neuro-radiosurgery, were retrospectively analyzed. A framework for the evaluation of multimodal PET/MRI segmentation is also presented. Overlap-based and spatial distance-based metrics were considered to quantify similarity concerning PET and MRI segmentation approaches. Statistics was also included to measure correlation among the different segmentation processes. Since it is not possible to define a gold-standard CTV according to both MRI and PET images without treatment response assessment

A B-spline image registration based CAD scheme to evaluate drug treatment response of ovarian cancer patients

NASA Astrophysics Data System (ADS)

Tan, Maxine; Li, Zheng; Moore, Kathleen; Thai, Theresa; Ding, Kai; Liu, Hong; Zheng, Bin

2016-03-01

Ovarian cancer is the second most common cancer amongst gynecologic malignancies, and has the highest death rate. Since the majority of ovarian cancer patients (>75%) are diagnosed in the advanced stage with tumor metastasis, chemotherapy is often required after surgery to remove the primary ovarian tumors. In order to quickly assess patient response to the chemotherapy in the clinical trials, two sets of CT examinations are taken pre- and post-therapy (e.g., after 6 weeks). Treatment efficacy is then evaluated based on Response Evaluation Criteria in Solid Tumors (RECIST) guideline, whereby tumor size is measured by the longest diameter on one CT image slice and only a subset of selected tumors are tracked. However, this criterion cannot fully represent the volumetric changes of the tumors and might miss potentially problematic unmarked tumors. Thus, we developed a new CAD approach to measure and analyze volumetric tumor growth/shrinkage using a cubic B-spline deformable image registration method. In this initial study, on 14 sets of pre- and post-treatment CT scans, we registered the two consecutive scans using cubic B-spline registration in a multiresolution (from coarse to fine) framework. We used Mattes mutual information metric as the similarity criterion and the L-BFGS-B optimizer. The results show that our method can quantify volumetric changes in the tumors more accurately than RECIST, and also detect (highlight) potentially problematic regions that were not originally targeted by radiologists. Despite the encouraging results of this preliminary study, further validation of scheme performance is required using large and diverse datasets in future.

MO-B-BRC-00: Prostate HDR Treatment Planning - Considering Different Imaging Modalities

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

NONE

2016-06-15

Brachytherapy has proven to be an effective treatment option for prostate cancer. Initially, prostate brachytherapy was delivered through permanently implanted low dose rate (LDR) radioactive sources; however, high dose rate (HDR) temporary brachytherapy for prostate cancer is gaining popularity. Needle insertion during prostate brachytherapy is most commonly performed under ultrasound (U/S) guidance; however, treatment planning may be performed utilizing several imaging modalities either in an intra- or post-operative setting. During intra-operative prostate HDR, the needles are imaged during implantation, and planning may be performed in real time. At present, the most common imaging modality utilized for intra-operative prostate HDR ismore » U/S. Alternatively, in the post-operative setting, following needle implantation, patients may be simulated with computed tomography (CT) or magnetic resonance imaging (MRI). Each imaging modality and workflow provides its share of benefits and limitations. Prostate HDR has been adopted in a number of cancer centers across the nation. In this educational session, we will explore the role of U/S, CT, and MRI in HDR prostate brachytherapy. Example workflows and operational details will be shared, and we will discuss how to establish a prostate HDR program in a clinical setting. Learning Objectives: Review prostate HDR techniques based on the imaging modality Discuss the challenges and pitfalls introduced by the three imagebased options for prostate HDR brachytherapy Review the QA process and learn about the development of clinical workflows for these imaging options at different institutions.« less

Infrared imaging-based combat casualty care system

NASA Astrophysics Data System (ADS)

Davidson, James E., Sr.

1997-08-01

A Small Business Innovative Research (SBIR) contract was recently awarded to a start up company for the development of an infrared (IR) image based combat casualty care system. The company, Medical Thermal Diagnostics, or MTD, is developing a light weight, hands free, energy efficient uncooled IR imaging system based upon a Texas Instruments design which will allow emergency medical treatment of wounded soldiers in complete darkness without any type of light enhancement equipment. The principal investigator for this effort, Dr. Gene Luther, DVM, Ph.D., Professor Emeritus, LSU School of Veterinary Medicine, will conduct the development and testing of this system with support from Thermalscan, Inc., a nondestructive testing company experienced in IR thermography applications. Initial research has been done with surgery on a cat for feasibility of the concept as well as forensic research on pigs as a close representation of human physiology to determine time of death. Further such studies will be done later as well as trauma studies. IR images of trauma injuries will be acquired by imaging emergency room patients to create an archive of emergency medical situations seen with an infrared imaging camera. This archived data will then be used to develop training material for medical personnel using the system. This system has potential beyond military applications. Firefighters and emergency medical technicians could directly benefit from the capability to triage and administer medical care to trauma victims in low or no light conditions.

Snapping hip: imaging and treatment.

PubMed

Lee, Kenneth S; Rosas, Humberto G; Phancao, Jean-Pierre

2013-07-01

Snapping hip, or coxa saltans, presents as an audible or palpable snapping that occurs around the hip during movement and can be associated with or without pain. The prevalence of snapping hip is estimated to occur in up to 10% of the general population, but it is especially seen in athletes such as dancers, soccer players, weight lifters, and runners. Although the snapping sound can be readily heard, the diagnostic cause may be a clinical challenge. The causes of snapping hip have been divided into two distinct categories: extra-articular and intra-articular. Extra-articular snapping hip can be further subdivided into external and internal causes. Advances in imaging techniques have improved the diagnostic accuracy of the various causes of snapping hip, mainly by providing real-time imaging evaluation of moving structures during the snapping phase. Image-guided treatments have also been useful in the diagnostic work-up of snapping hip given the complexity and multitude of causes of hip pain. We discuss the common and uncommon causes of snapping hip, the advanced imaging techniques that now give us a better understanding of the underlying mechanism, and an image-guided diagnostic and therapeutic algorithm that helps to identify surgical candidates. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

CT-image-based conformal brachytherapy of breast cancer. The significance of semi-3-D and 3-D treatment planning.

PubMed

Polgár, C; Major, T; Somogyi, A; Takácsi-Nagy, Z; Mangel, L C; Forrai, G; Sulyok, Z; Fodor, J; Németh, G

2000-03-01

To compare the conventional 2-D, the simulator-guided semi-3-D and the recently developed CT-guided 3-D brachytherapy treatment planning in the interstitial radiotherapy of breast cancer. In 103 patients with T1-2, N0-1 breast cancer the tumor bed was clipped during breast conserving surgery. Fifty-two of them received boost brachytherapy after 46 to 50 Gy teletherapy and 51 patients were treated with brachytherapy alone via flexible implant tubes. Single, double and triple plane implant was used in 6, 89 and 8 cases, respectively. The dose of boost brachytherapy and sole brachytherapy prescribed to dose reference points was 3 times 4.75 Gy and 7 times 5.2 Gy, respectively. The positions of dose reference points varied according to the level (2-D, semi-3-D and 3-D) of treatment planning performed. The treatment planning was based on the 3-D reconstruction of the surgical clips, implant tubes and skin points. In all cases the implantations were planned with a semi-3-D technique aided by simulator. In 10 cases a recently developed CT-guided 3-D planning system was used. The semi-3-D and 3-D treatment plans were compared to hypothetical 2-D plans using dose-volume histograms and dose non-uniformity ratios. The values of mean central dose, mean skin dose, minimal clip dose, proportion of underdosaged clips and mean target surface dose were evaluated. The accuracy of tumor bed localization and the conformity of planning target volume and treated volume were also analyzed in each technique. With the help of conformal semi-3-D and 3-D brachytherapy planning we could define reference dose points, active source positions and dwell times individually. This technique decreased the mean skin dose with 22.2% and reduced the possibility of geographical miss. We could achieve the best conformity between the planning target volume and the treated volume with the CT-image based 3-D treatment planning, at the cost of worse dose homogeneity. The mean treated volume was reduced by 25

The Life Cycle of Images: Revisiting the Ethical Treatment of the Art Therapy Image

ERIC Educational Resources Information Center

Hinz, Lisa D.

2013-01-01

Using the metaphor of the human life cycle, the author of this viewpoint suggests that consideration of the birth, life, and death of images made in art therapy may promote a new perspective on their ethical treatment. A developmental view of images encourages art therapists to see art images as living entities that undergo a natural life cycle.…

PEGylated Peptide-Based Imaging Agents for Targeted Molecular Imaging.

PubMed

Wu, Huizi; Huang, Jiaguo

2016-01-01

Molecular imaging is able to directly visualize targets and characterize cellular pathways with a high signal/background ratio, which requires a sufficient amount of agents to uptake and accumulate in the imaging area. The design and development of peptide based agents for imaging and diagnosis as a hot and promising research topic that is booming in the field of molecular imaging. To date, selected peptides have been increasingly developed as agents by coupling with different imaging moieties (such as radiometals and fluorophore) with the help of sophisticated chemical techniques. Although a few successes have been achieved, most of them have failed mainly caused by their fast renal clearance and therefore low tumor uptakes, which may limit the effectively tumor retention effect. Besides, several peptide agents based on nanoparticles have also been developed for medical diagnostics. However, a great majority of those agents shown long circulation times and accumulation over time into the reticuloendothelial system (RES; including spleen, liver, lymph nodes and bone marrow) after systematic administration, such long-term severe accumulation probably results in the possible likelihood of toxicity and potentially induces health hazards. Recently reported design criteria have been proposed not only to enhance binding affinity in tumor region with long retention, but also to improve clearance from the body in a reasonable amount of time. PEGylation has been considered as one of the most successful modification methods to prolong tumor retention and improve the pharmacokinetic and pharmacodynamic properties for peptide-based imaging agents. This review summarizes an overview of PEGylated peptides imaging agents based on different imaging moieties including radioisotopes, fluorophores, and nanoparticles. The unique concepts and applications of various PEGylated peptide-based imaging agents are introduced for each of several imaging moieties. Effects of PEGylation on

Plantar fascia: imaging diagnosis and guided treatment.

PubMed

McNally, Eugene G; Shetty, Shilpa

2010-09-01

Plantar fasciopathy is a common cause of heel pain. This article covers the imaging anatomy of the hindfoot, the imaging findings on ultrasound and magnetic resonance imaging (MRI) of plantar fasciopathy, plantar fibromas, trauma, Achilles tendonopathy, neural compression, stress fractures of the os calcis and other heel pad lesions. Thickening of the plantar fascia insertion more than 5 mm either on ultrasound or MRI is suggestive of plantar fasciopathy. Ultrasound is superior to MRI for diagnosis of plantar fibroma as small low signal lesions on MRI are similar to the normal plantar fascia signal. Ultrasound demonstrates low echogenicity compared with the echogenic plantar fascia. Penetrating injuries can appear bizarre due to associated foreign body impaction and infection. Achilles tendonopathy can cause heel pain and should be considered as a possible diagnosis. Treatment options include physical therapy, ECSWT, corticosteroid injection, and dry needling. Percutaneous US guided treatment methods will be described. Thieme Medical Publishers.

Retrospective analysis of imaging techniques for treatment planning and monitoring of obliteration for gamma knife treatment of cerebral arteriovenous malformation.

PubMed

Amponsah, Kwame; Ellis, Thomas L; Chan, Michael D; Lovato, James F; Bourland, J Daniel; deGuzman, Allan F; Ekstrand, Kenneth E; Munley, Michael T; McMullen, Kevin P; Shaw, Edward G; Tatter, Stephen B

2012-10-01

It has been well established that Gamma Knife radiosurgery (GKS) is an effective treatment for brain arteriovenous malformations (AVMs). To evaluate complete obliteration rates for magnetic resonance imaging (MRI)-based GKS treatment planning performed with and without angiography and to conduct a preliminary assessment of the utility of using pulsed arterial spin labeling (PASL) magnetic resonance (MR) perfusion imaging to confirm complete obliteration. Forty-six patients were identified who had undergone GKS without embolization with a minimum follow-up of 2 years. One group was planned with integrated stereotactic angiography and MR (spoiled gradient recalled) images obtained on the day of GKS. A second technique avoided the risk of arteriography by using only axial MR images. Beginning in 2007, PASL MR perfusion imaging was routinely performed as a portion of the follow-up MRI to assess the restoration of normal blood flow of the nidus and surrounding area. The overall obliteration rate for the angiography/MRI group was 88.0% (29 of 33). Patients in the MRI-only group had an obliteration rate of 61.5% (8 of 13), with P=.092 with the Fisher exact test, which is not statistically significant. A Kaplan-Meier analysis was also not statistically significant (log rank test, P=.474). Four of 9 patients with incomplete obliteration on angiography also had shown residual abnormal blood flow on PASL imaging. This retrospective analysis shows that treatment planning technique used in GKS does not play a role in the eventual obliteration of treated AVMs. PASL may have potential in the evaluation of AVM obliteration.

Nanoparticles for imaging and treatment of metastatic breast cancer

PubMed Central

Mu, Qingxin; Wang, Hui; Zhang, Miqin

2017-01-01

Introduction Metastatic breast cancer is one of the most devastating cancers that have no cure. Many therapeutic and diagnostic strategies have been extensively studied in the past decade. Among these strategies, cancer nanotechnology has emerged as a promising strategy in preclinical studies by enabling early identification of primary tumors and metastases, and by effective killing of cancer cells. Areas covered This review covers the recent progress made in targeting and imaging of metastatic breast cancer with nanoparticles, and treatment using nanoparticle-enabled chemo-, gene, photothermal- and radio-therapies. This review also discusses recent developments of nanoparticle-enabled stem cell therapy and immunotherapy. Expert opinion Nanotechnology is expected to play important roles in modern therapy for cancers, including metastatic breast cancer. Nanoparticles are able to target and visualize metastasis in various organs, and deliver therapeutic agents. Through targeting cancer stem cells, nanoparticles are able to treat resistant tumors with minimal toxicity to healthy tissues/organs. Nanoparticles are also able to activate immune cells to eliminate tumors. Owing to their multifunctional, controllable and trackable features, nanotechnology-based imaging and therapy could be a highly potent approach for future cancer research and treatment. PMID:27401941

Knowledge-Based Image Analysis.

DTIC Science & Technology

1981-04-01

UNCLASSIF1 ED ETL-025s N IIp ETL-0258 AL Ai01319 S"Knowledge-based image analysis u George C. Stockman Barbara A. Lambird I David Lavine Laveen N. Kanal...extraction, verification, region classification, pattern recognition, image analysis . 3 20. A. CT (Continue on rever.. d. It necessary and Identify by...UNCLgSTFTF n In f SECURITY CLASSIFICATION OF THIS PAGE (When Date Entered) .L1 - I Table of Contents Knowledge Based Image Analysis I Preface

Sensitivity study of voxel-based PET image comparison to image registration algorithms

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

Yip, Stephen, E-mail: syip@lroc.harvard.edu; Chen, Aileen B.; Berbeco, Ross

2014-11-01

Purpose: Accurate deformable registration is essential for voxel-based comparison of sequential positron emission tomography (PET) images for proper adaptation of treatment plan and treatment response assessment. The comparison may be sensitive to the method of deformable registration as the optimal algorithm is unknown. This study investigated the impact of registration algorithm choice on therapy response evaluation. Methods: Sixteen patients with 20 lung tumors underwent a pre- and post-treatment computed tomography (CT) and 4D FDG-PET scans before and after chemoradiotherapy. All CT images were coregistered using a rigid and ten deformable registration algorithms. The resulting transformations were then applied to themore » respective PET images. Moreover, the tumor region defined by a physician on the registered PET images was classified into progressor, stable-disease, and responder subvolumes. Particularly, voxels with standardized uptake value (SUV) decreases >30% were classified as responder, while voxels with SUV increases >30% were progressor. All other voxels were considered stable-disease. The agreement of the subvolumes resulting from difference registration algorithms was assessed by Dice similarity index (DSI). Coefficient of variation (CV) was computed to assess variability of DSI between individual tumors. Root mean square difference (RMS{sub rigid}) of the rigidly registered CT images was used to measure the degree of tumor deformation. RMS{sub rigid} and DSI were correlated by Spearman correlation coefficient (R) to investigate the effect of tumor deformation on DSI. Results: Median DSI{sub rigid} was found to be 72%, 66%, and 80%, for progressor, stable-disease, and responder, respectively. Median DSI{sub deformable} was 63%–84%, 65%–81%, and 82%–89%. Variability of DSI was substantial and similar for both rigid and deformable algorithms with CV > 10% for all subvolumes. Tumor deformation had moderate to significant impact on DSI for

Segmentation Approach Towards Phase-Contrast Microscopic Images of Activated Sludge to Monitor the Wastewater Treatment.

PubMed

Khan, Muhammad Burhan; Nisar, Humaira; Ng, Choon Aun; Yeap, Kim Ho; Lai, Koon Chun

2017-12-01

Image processing and analysis is an effective tool for monitoring and fault diagnosis of activated sludge (AS) wastewater treatment plants. The AS image comprise of flocs (microbial aggregates) and filamentous bacteria. In this paper, nine different approaches are proposed for image segmentation of phase-contrast microscopic (PCM) images of AS samples. The proposed strategies are assessed for their effectiveness from the perspective of microscopic artifacts associated with PCM. The first approach uses an algorithm that is based on the idea that different color space representation of images other than red-green-blue may have better contrast. The second uses an edge detection approach. The third strategy, employs a clustering algorithm for the segmentation and the fourth applies local adaptive thresholding. The fifth technique is based on texture-based segmentation and the sixth uses watershed algorithm. The seventh adopts a split-and-merge approach. The eighth employs Kittler's thresholding. Finally, the ninth uses a top-hat and bottom-hat filtering-based technique. The approaches are assessed, and analyzed critically with reference to the artifacts of PCM. Gold approximations of ground truth images are prepared to assess the segmentations. Overall, the edge detection-based approach exhibits the best results in terms of accuracy, and the texture-based algorithm in terms of false negative ratio. The respective scenarios are explained for suitability of edge detection and texture-based algorithms.

Image based Monte Carlo Modeling for Computational Phantom

NASA Astrophysics Data System (ADS)

Cheng, Mengyun; Wang, Wen; Zhao, Kai; Fan, Yanchang; Long, Pengcheng; Wu, Yican

2014-06-01

The evaluation on the effects of ionizing radiation and the risk of radiation exposure on human body has been becoming one of the most important issues for radiation protection and radiotherapy fields, which is helpful to avoid unnecessary radiation and decrease harm to human body. In order to accurately evaluate the dose on human body, it is necessary to construct more realistic computational phantom. However, manual description and verfication of the models for Monte carlo(MC)simulation are very tedious, error-prone and time-consuming. In addiation, it is difficult to locate and fix the geometry error, and difficult to describe material information and assign it to cells. MCAM (CAD/Image-based Automatic Modeling Program for Neutronics and Radiation Transport Simulation) was developed as an interface program to achieve both CAD- and image-based automatic modeling by FDS Team (Advanced Nuclear Energy Research Team, http://www.fds.org.cn). The advanced version (Version 6) of MCAM can achieve automatic conversion from CT/segmented sectioned images to computational phantoms such as MCNP models. Imaged-based automatic modeling program(MCAM6.0) has been tested by several medical images and sectioned images. And it has been applied in the construction of Rad-HUMAN. Following manual segmentation and 3D reconstruction, a whole-body computational phantom of Chinese adult female called Rad-HUMAN was created by using MCAM6.0 from sectioned images of a Chinese visible human dataset. Rad-HUMAN contains 46 organs/tissues, which faithfully represented the average anatomical characteristics of the Chinese female. The dose conversion coefficients(Dt/Ka) from kerma free-in-air to absorbed dose of Rad-HUMAN were calculated. Rad-HUMAN can be applied to predict and evaluate dose distributions in the Treatment Plan System (TPS), as well as radiation exposure for human body in radiation protection.

2-D Myocardial Deformation Imaging Based on RF-Based Nonrigid Image Registration.

PubMed

Chakraborty, Bidisha; Liu, Zhi; Heyde, Brecht; Luo, Jianwen; D'hooge, Jan

2018-06-01

Myocardial deformation imaging is a well-established echocardiographic technique for the assessment of myocardial function. Although some solutions make use of speckle tracking of the reconstructed B-mode images, others apply block matching (BM) on the underlying radio frequency (RF) data in order to increase sensitivity to small interframe motion and deformation. However, for both approaches, lateral motion estimation remains a challenge due to the relatively poor lateral resolution of the ultrasound image in combination with the lack of phase information in this direction. Hereto, nonrigid image registration (NRIR) of B-mode images has previously been proposed as an attractive solution. However, hereby, the advantages of RF-based tracking were lost. The aim of this paper was, therefore, to develop an NRIR motion estimator adapted to RF data sets. The accuracy of this estimator was quantified using synthetic data and was contrasted against a state-of-the-art BM solution. The results show that RF-based NRIR outperforms BM in terms of tracking accuracy, particularly, as hypothesized, in the lateral direction. Finally, this RF-based NRIR algorithm was applied clinically, illustrating its ability to estimate both in-plane velocity components in vivo.

Prostate-specific membrane antigen-based imaging in prostate cancer: impact on clinical decision making process.

PubMed

Demirkol, Mehmet Onur; Acar, Ömer; Uçar, Burcu; Ramazanoğlu, Sultan Rana; Sağlıcan, Yeşim; Esen, Tarık

2015-05-01

There is an ongoing need for an accurate imaging modality which can be used for staging purposes, metastatic evaluation, predicting biologic aggresiveness and investigating recurrent disease in prostate cancer. Prostate specific membrane antigen, given its favorable molecular characteristics, holds a promise as an ideal target for prostate cancer-specific nuclear imaging. In this study, we evaluated our initial results of PSMA based PET/CT imaging in prostate cancer. A total of 22 patients with a median age and serum PSA level of 68 years and 4.15 ng/ml, respectively underwent Ga-68 PSMA PET/CT in our hospital between Februrary and August 2014. Their charts were retrospectively reviewed in order to document the clinical characteristics, the indications for and the results of PSMA based imaging and the impact of Ga-68 PSMA PET/CT findings on disease management. The most common indications were rising PSA after local ± adjuvant treatment followed by staging and metastatic evaluation before definitive or salvage treatment. All except 2 patients had prostatic ± extraprostatic PSMA positive lesions. For those who had a positive result; treatment strategies were tailored accordingly. Above the PSA level of 2 ng/ml, none of the PSMA based nuclear imaging studies revealed negative results. PSMA based nuclear imaging has significantly impacted our way of handling patients with prostate cancer. Its preliminary performance in different clinical scenarios and ability to detect lesions even in low PSA values seems fairly promising and deserves to be supplemented with further clinical studies. © 2015 Wiley Periodicals, Inc.

Differentiating tumor recurrence from treatment necrosis: a review of neuro-oncologic imaging strategies

PubMed Central

Verma, Nishant; Cowperthwaite, Matthew C.; Burnett, Mark G.; Markey, Mia K.

2013-01-01

Abstract Differentiating treatment-induced necrosis from tumor recurrence is a central challenge in neuro-oncology. These 2 very different outcomes after brain tumor treatment often appear similarly on routine follow-up imaging studies. They may even manifest with similar clinical symptoms, further confounding an already difficult process for physicians attempting to characterize a new contrast-enhancing lesion appearing on a patient's follow-up imaging. Distinguishing treatment necrosis from tumor recurrence is crucial for diagnosis and treatment planning, and therefore, much effort has been put forth to develop noninvasive methods to differentiate between these disparate outcomes. In this article, we review the latest developments and key findings from research studies exploring the efficacy of structural and functional imaging modalities for differentiating treatment necrosis from tumor recurrence. We discuss the possibility of computational approaches to investigate the usefulness of fine-grained imaging characteristics that are difficult to observe through visual inspection of images. We also propose a flexible treatment-planning algorithm that incorporates advanced functional imaging techniques when indicated by the patient's routine follow-up images and clinical condition. PMID:23325863

Log-Gabor Energy Based Multimodal Medical Image Fusion in NSCT Domain

PubMed Central

Yang, Yong; Tong, Song; Huang, Shuying; Lin, Pan

2014-01-01

Multimodal medical image fusion is a powerful tool in clinical applications such as noninvasive diagnosis, image-guided radiotherapy, and treatment planning. In this paper, a novel nonsubsampled Contourlet transform (NSCT) based method for multimodal medical image fusion is presented, which is approximately shift invariant and can effectively suppress the pseudo-Gibbs phenomena. The source medical images are initially transformed by NSCT followed by fusing low- and high-frequency components. The phase congruency that can provide a contrast and brightness-invariant representation is applied to fuse low-frequency coefficients, whereas the Log-Gabor energy that can efficiently determine the frequency coefficients from the clear and detail parts is employed to fuse the high-frequency coefficients. The proposed fusion method has been compared with the discrete wavelet transform (DWT), the fast discrete curvelet transform (FDCT), and the dual tree complex wavelet transform (DTCWT) based image fusion methods and other NSCT-based methods. Visually and quantitatively experimental results indicate that the proposed fusion method can obtain more effective and accurate fusion results of multimodal medical images than other algorithms. Further, the applicability of the proposed method has been testified by carrying out a clinical example on a woman affected with recurrent tumor images. PMID:25214889

Validation of a method for in vivo 3D dose reconstruction for IMRT and VMAT treatments using on-treatment EPID images and a model-based forward-calculation algorithm

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

Van Uytven, Eric, E-mail: eric.vanuytven@cancercare.mb.ca; Van Beek, Timothy; McCowan, Peter M.

2015-12-15

Purpose: Radiation treatments are trending toward delivering higher doses per fraction under stereotactic radiosurgery and hypofractionated treatment regimens. There is a need for accurate 3D in vivo patient dose verification using electronic portal imaging device (EPID) measurements. This work presents a model-based technique to compute full three-dimensional patient dose reconstructed from on-treatment EPID portal images (i.e., transmission images). Methods: EPID dose is converted to incident fluence entering the patient using a series of steps which include converting measured EPID dose to fluence at the detector plane and then back-projecting the primary source component of the EPID fluence upstream of themore » patient. Incident fluence is then recombined with predicted extra-focal fluence and used to calculate 3D patient dose via a collapsed-cone convolution method. This method is implemented in an iterative manner, although in practice it provides accurate results in a single iteration. The robustness of the dose reconstruction technique is demonstrated with several simple slab phantom and nine anthropomorphic phantom cases. Prostate, head and neck, and lung treatments are all included as well as a range of delivery techniques including VMAT and dynamic intensity modulated radiation therapy (IMRT). Results: Results indicate that the patient dose reconstruction algorithm compares well with treatment planning system computed doses for controlled test situations. For simple phantom and square field tests, agreement was excellent with a 2%/2 mm 3D chi pass rate ≥98.9%. On anthropomorphic phantoms, the 2%/2 mm 3D chi pass rates ranged from 79.9% to 99.9% in the planning target volume (PTV) region and 96.5% to 100% in the low dose region (>20% of prescription, excluding PTV and skin build-up region). Conclusions: An algorithm to reconstruct delivered patient 3D doses from EPID exit dosimetry measurements was presented. The method was applied to phantom and

Imaging of skull base lesions.

PubMed

Kelly, Hillary R; Curtin, Hugh D

2016-01-01

Skull base imaging requires a thorough knowledge of the complex anatomy of this region, including the numerous fissures and foramina and the major neurovascular structures that traverse them. Computed tomography (CT) and magnetic resonance imaging (MRI) play complementary roles in imaging of the skull base. MR is the preferred modality for evaluation of the soft tissues, the cranial nerves, and the medullary spaces of bone, while CT is preferred for demonstrating thin cortical bone structure. The anatomic location and origin of a lesion as well as the specific CT and MR findings can often narrow the differential diagnosis to a short list of possibilities. However, the primary role of the imaging specialist in evaluating the skull base is usually to define the extent of the lesion and determine its relationship to vital neurovascular structures. Technologic advances in imaging and radiation therapy, as well as surgical technique, have allowed for more aggressive approaches and improved outcomes, further emphasizing the importance of precise preoperative mapping of skull base lesions via imaging. Tumors arising from and affecting the cranial nerves at the skull base are considered here. © 2016 Elsevier B.V. All rights reserved.

Superpixel-based classification of gastric chromoendoscopy images

NASA Astrophysics Data System (ADS)

Boschetto, Davide; Grisan, Enrico

2017-03-01

Chromoendoscopy (CH) is a gastroenterology imaging modality that involves the staining of tissues with methylene blue, which reacts with the internal walls of the gastrointestinal tract, improving the visual contrast in mucosal surfaces and thus enhancing a doctor's ability to screen precancerous lesions or early cancer. This technique helps identify areas that can be targeted for biopsy or treatment and in this work we will focus on gastric cancer detection. Gastric chromoendoscopy for cancer detection has several taxonomies available, one of which classifies CH images into three classes (normal, metaplasia, dysplasia) based on color, shape and regularity of pit patterns. Computer-assisted diagnosis is desirable to help us improve the reliability of the tissue classification and abnormalities detection. However, traditional computer vision methodologies, mainly segmentation, do not translate well to the specific visual characteristics of a gastroenterology imaging scenario. We propose the exploitation of a first unsupervised segmentation via superpixel, which groups pixels into perceptually meaningful atomic regions, used to replace the rigid structure of the pixel grid. For each superpixel, a set of features is extracted and then fed to a random forest based classifier, which computes a model used to predict the class of each superpixel. The average general accuracy of our model is 92.05% in the pixel domain (86.62% in the superpixel domain), while detection accuracies on the normal and abnormal class are respectively 85.71% and 95%. Eventually, the whole image class can be predicted image through a majority vote on each superpixel's predicted class.

Processing and refinement of steel microstructure images for assisting in computerized heat treatment of plain carbon steel

NASA Astrophysics Data System (ADS)

Gupta, Shubhank; Panda, Aditi; Naskar, Ruchira; Mishra, Dinesh Kumar; Pal, Snehanshu

2017-11-01

Steels are alloys of iron and carbon, widely used in construction and other applications. The evolution of steel microstructure through various heat treatment processes is an important factor in controlling properties and performance of steel. Extensive experimentations have been performed to enhance the properties of steel by customizing heat treatment processes. However, experimental analyses are always associated with high resource requirements in terms of cost and time. As an alternative solution, we propose an image processing-based technique for refinement of raw plain carbon steel microstructure images, into a digital form, usable in experiments related to heat treatment processes of steel in diverse applications. The proposed work follows the conventional steps practiced by materials engineers in manual refinement of steel images; and it appropriately utilizes basic image processing techniques (including filtering, segmentation, opening, and clustering) to automate the whole process. The proposed refinement of steel microstructure images is aimed to enable computer-aided simulations of heat treatment of plain carbon steel, in a timely and cost-efficient manner; hence it is beneficial for the materials and metallurgy industry. Our experimental results prove the efficiency and effectiveness of the proposed technique.

A system for EPID-based real-time treatment delivery verification during dynamic IMRT treatment.

PubMed

Fuangrod, Todsaporn; Woodruff, Henry C; van Uytven, Eric; McCurdy, Boyd M C; Kuncic, Zdenka; O'Connor, Daryl J; Greer, Peter B

2013-09-01

To design and develop a real-time electronic portal imaging device (EPID)-based delivery verification system for dynamic intensity modulated radiation therapy (IMRT) which enables detection of gross treatment delivery errors before delivery of substantial radiation to the patient. The system utilizes a comprehensive physics-based model to generate a series of predicted transit EPID image frames as a reference dataset and compares these to measured EPID frames acquired during treatment. The two datasets are using MLC aperture comparison and cumulative signal checking techniques. The system operation in real-time was simulated offline using previously acquired images for 19 IMRT patient deliveries with both frame-by-frame comparison and cumulative frame comparison. Simulated error case studies were used to demonstrate the system sensitivity and performance. The accuracy of the synchronization method was shown to agree within two control points which corresponds to approximately ∼1% of the total MU to be delivered for dynamic IMRT. The system achieved mean real-time gamma results for frame-by-frame analysis of 86.6% and 89.0% for 3%, 3 mm and 4%, 4 mm criteria, respectively, and 97.9% and 98.6% for cumulative gamma analysis. The system can detect a 10% MU error using 3%, 3 mm criteria within approximately 10 s. The EPID-based real-time delivery verification system successfully detected simulated gross errors introduced into patient plan deliveries in near real-time (within 0.1 s). A real-time radiation delivery verification system for dynamic IMRT has been demonstrated that is designed to prevent major mistreatments in modern radiation therapy.

A novel content-based medical image retrieval method based on query topic dependent image features (QTDIF)

NASA Astrophysics Data System (ADS)

Xiong, Wei; Qiu, Bo; Tian, Qi; Mueller, Henning; Xu, Changsheng

2005-04-01

Medical image retrieval is still mainly a research domain with a large variety of applications and techniques. With the ImageCLEF 2004 benchmark, an evaluation framework has been created that includes a database, query topics and ground truth data. Eleven systems (with a total of more than 50 runs) compared their performance in various configurations. The results show that there is not any one feature that performs well on all query tasks. Key to successful retrieval is rather the selection of features and feature weights based on a specific set of input features, thus on the query task. In this paper we propose a novel method based on query topic dependent image features (QTDIF) for content-based medical image retrieval. These feature sets are designed to capture both inter-category and intra-category statistical variations to achieve good retrieval performance in terms of recall and precision. We have used Gaussian Mixture Models (GMM) and blob representation to model medical images and construct the proposed novel QTDIF for CBIR. Finally, trained multi-class support vector machines (SVM) are used for image similarity ranking. The proposed methods have been tested over the Casimage database with around 9000 images, for the given 26 image topics, used for imageCLEF 2004. The retrieval performance has been compared with the medGIFT system, which is based on the GNU Image Finding Tool (GIFT). The experimental results show that the proposed QTDIF-based CBIR can provide significantly better performance than systems based general features only.

Automatic medical image annotation and keyword-based image retrieval using relevance feedback.

PubMed

Ko, Byoung Chul; Lee, JiHyeon; Nam, Jae-Yeal

2012-08-01

This paper presents novel multiple keywords annotation for medical images, keyword-based medical image retrieval, and relevance feedback method for image retrieval for enhancing image retrieval performance. For semantic keyword annotation, this study proposes a novel medical image classification method combining local wavelet-based center symmetric-local binary patterns with random forests. For keyword-based image retrieval, our retrieval system use the confidence score that is assigned to each annotated keyword by combining probabilities of random forests with predefined body relation graph. To overcome the limitation of keyword-based image retrieval, we combine our image retrieval system with relevance feedback mechanism based on visual feature and pattern classifier. Compared with other annotation and relevance feedback algorithms, the proposed method shows both improved annotation performance and accurate retrieval results.

Integrated photoacoustic/ultrasound/HFU system based on a clinical ultrasound imaging platform

NASA Astrophysics Data System (ADS)

Kim, Jeesu; Choi, Wonseok; Park, Eun-Yeong; Kim, Chulhong

2018-02-01

Non-invasive treatment of tumor is beneficial for the favorable prognosis of the patients. High Intensity Focused Ultrasound (HIFU) is an emerging non-invasive treatment tool that ablates tumor lesions by increasing local temperature without damaging surrounding tissues. In HIFU therapy, accurate focusing of the HIFU energy into the target lesion and real-time assessment of thermal distribution are critical for successful and safe treatment. Photoacoustic (PA) imaging is a novel biomedical imaging technique that can visualize functional information of biological tissues based on optical absorption and thermoelastic expansion. One unique feature of PA imaging is that the amplitude of the PA signal reflects the local temperature. Here, we demonstrate a real-time temperature monitoring system that can evaluate thermal distribution during HIFU therapy. We have integrated a HIFU treatment system, a clinical ultrasound (US) machine, and a tunable laser system and have acquired real-time PA/US images of in vitro phantoms and in vivo animals during HIFU therapy without interference from the therapeutic US waves. We have also evaluated the temperature monitoring capability of the system by comparing the amplitude of PA signals with the measured temperature in melanoma tumor bearing mice. Although much more updates are required for clinical applications, the results show the promising potential of the system to ensure accurate and safe HIFU therapy by monitoring the thermal distribution of the treatment area.

Automatic tissue segmentation of head and neck MR images for hyperthermia treatment planning

NASA Astrophysics Data System (ADS)

Fortunati, Valerio; Verhaart, René F.; Niessen, Wiro J.; Veenland, Jifke F.; Paulides, Margarethus M.; van Walsum, Theo

2015-08-01

A hyperthermia treatment requires accurate, patient-specific treatment planning. This planning is based on 3D anatomical models which are generally derived from computed tomography. Because of its superior soft tissue contrast, magnetic resonance imaging (MRI) information can be introduced to improve the quality of these 3D patient models and therefore the treatment planning itself. Thus, we present here an automatic atlas-based segmentation algorithm for MR images of the head and neck. Our method combines multiatlas local weighting fusion with intensity modelling. The accuracy of the method was evaluated using a leave-one-out cross validation experiment over a set of 11 patients for which manual delineation were available. The accuracy of the proposed method was high both in terms of the Dice similarity coefficient (DSC) and the 95th percentile Hausdorff surface distance (HSD) with median DSC higher than 0.8 for all tissues except sclera. For all tissues, except the spine tissues, the accuracy was approaching the interobserver agreement/variability both in terms of DSC and HSD. The positive effect of adding the intensity modelling to the multiatlas fusion decreased when a more accurate atlas fusion method was used. Using the proposed approach we improved the performance of the approach previously presented for H&N hyperthermia treatment planning, making the method suitable for clinical application.

Application of Magnetic Resonance Imaging and Three-Dimensional Treatment Planning in the Treatment of Orbital Lymphoma

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

Rudoltz, Marc S.; Ayyangar, Komanduri; Mohiuddin, Mohammed

Radiotherapy for lymphoma of the orbit must be individualized for each patient and clinical setting. Most techniques focus on optimizing the dose to the tumor while sparing the lens. This study describes a technique utilizing magnetic resonance imaging (MRI) and three dimensional (3D) planning in the treatment of orbital lymphoma. A patient presented with an intermediate grade lymphoma of the right orbit. The prescribed tumor dose was 4050 cGy in 18 fractions. Three D planning was carried out and tumor volumes, retina, and lens were subsequently outlined. Dose calculations including dose volume histograms of the target, retina, and lens weremore » then performed. Part of the retina was outside of the treatment volume while 50% of the retina received 90% or more of the prescribed dose. The patient was clinically NED when last seen 2 years following therapy with no treatment-related morbidity. Patients with lymphomas of the orbit can be optimally treated using MRI based 3D treatment planning.« less

Image-Based 3d Reconstruction and Analysis for Orthodontia

NASA Astrophysics Data System (ADS)

Knyaz, V. A.

2012-08-01

Among the main tasks of orthodontia are analysis of teeth arches and treatment planning for providing correct position for every tooth. The treatment plan is based on measurement of teeth parameters and designing perfect teeth arch curve which teeth are to create after treatment. The most common technique for teeth moving uses standard brackets which put on teeth and a wire of given shape which is clamped by these brackets for producing necessary forces to every tooth for moving it in given direction. The disadvantages of standard bracket technique are low accuracy of tooth dimensions measurements and problems with applying standard approach for wide variety of complex orthodontic cases. The image-based technique for orthodontic planning, treatment and documenting aimed at overcoming these disadvantages is proposed. The proposed approach provides performing accurate measurements of teeth parameters needed for adequate planning, designing correct teeth position and monitoring treatment process. The developed technique applies photogrammetric means for teeth arch 3D model generation, brackets position determination and teeth shifting analysis.

Review of ultrasound image guidance in external beam radiotherapy: I. Treatment planning and inter-fraction motion management

NASA Astrophysics Data System (ADS)

Fontanarosa, Davide; van der Meer, Skadi; Bamber, Jeffrey; Harris, Emma; O'Shea, Tuathan; Verhaegen, Frank

2015-02-01

In modern radiotherapy, verification of the treatment to ensure the target receives the prescribed dose and normal tissues are optimally spared has become essential. Several forms of image guidance are available for this purpose. The most commonly used forms of image guidance are based on kilovolt or megavolt x-ray imaging. Image guidance can also be performed with non-harmful ultrasound (US) waves. This increasingly used technique has the potential to offer both anatomical and functional information. This review presents an overview of the historical and current use of two-dimensional and three-dimensional US imaging for treatment verification in radiotherapy. The US technology and the implementation in the radiotherapy workflow are described. The use of US guidance in the treatment planning process is discussed. The role of US technology in inter-fraction motion monitoring and management is explained, and clinical studies of applications in areas such as the pelvis, abdomen and breast are reviewed. A companion review paper (O’Shea et al 2015 Phys. Med. Biol. submitted) will extensively discuss the use of US imaging for intra-fraction motion quantification and novel applications of US technology to RT.

Review of ultrasound image guidance in external beam radiotherapy: I. Treatment planning and inter-fraction motion management.

PubMed

Fontanarosa, Davide; van der Meer, Skadi; Bamber, Jeffrey; Harris, Emma; O'Shea, Tuathan; Verhaegen, Frank

2015-02-07

In modern radiotherapy, verification of the treatment to ensure the target receives the prescribed dose and normal tissues are optimally spared has become essential. Several forms of image guidance are available for this purpose. The most commonly used forms of image guidance are based on kilovolt or megavolt x-ray imaging. Image guidance can also be performed with non-harmful ultrasound (US) waves. This increasingly used technique has the potential to offer both anatomical and functional information.This review presents an overview of the historical and current use of two-dimensional and three-dimensional US imaging for treatment verification in radiotherapy. The US technology and the implementation in the radiotherapy workflow are described. The use of US guidance in the treatment planning process is discussed. The role of US technology in inter-fraction motion monitoring and management is explained, and clinical studies of applications in areas such as the pelvis, abdomen and breast are reviewed. A companion review paper (O'Shea et al 2015 Phys. Med. Biol. submitted) will extensively discuss the use of US imaging for intra-fraction motion quantification and novel applications of US technology to RT.

MO-FG-202-01: A Fast Yet Sensitive EPID-Based Real-Time Treatment Verification System

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

Ahmad, M; Nourzadeh, H; Neal, B

2016-06-15

Purpose: To create a real-time EPID-based treatment verification system which robustly detects treatment delivery and patient attenuation variations. Methods: Treatment plan DICOM files sent to the record-and-verify system are captured and utilized to predict EPID images for each planned control point using a modified GPU-based digitally reconstructed radiograph algorithm which accounts for the patient attenuation, source energy fluence, source size effects, and MLC attenuation. The DICOM and predicted images are utilized by our C++ treatment verification software which compares EPID acquired 1024×768 resolution frames acquired at ∼8.5hz from Varian Truebeam™ system. To maximize detection sensitivity, image comparisons determine (1) ifmore » radiation exists outside of the desired treatment field; (2) if radiation is lacking inside the treatment field; (3) if translations, rotations, and magnifications of the image are within tolerance. Acquisition was tested with known test fields and prior patient fields. Error detection was tested in real-time and utilizing images acquired during treatment with another system. Results: The computational time of the prediction algorithms, for a patient plan with 350 control points and 60×60×42cm^3 CT volume, is 2–3minutes on CPU and <27 seconds on GPU for 1024×768 images. The verification software requires a maximum of ∼9ms and ∼19ms for 512×384 and 1024×768 resolution images, respectively, to perform image analysis and dosimetric validations. Typical variations in geometric parameters between reference and the measured images are 0.32°for gantry rotation, 1.006 for scaling factor, and 0.67mm for translation. For excess out-of-field/missing in-field fluence, with masks extending 1mm (at isocenter) from the detected aperture edge, the average total in-field area missing EPID fluence was 1.5mm2 the out-of-field excess EPID fluence was 8mm^2, both below error tolerances. Conclusion: A real-time verification

World Wide Web Based Image Search Engine Using Text and Image Content Features

NASA Astrophysics Data System (ADS)

Luo, Bo; Wang, Xiaogang; Tang, Xiaoou

2003-01-01

Using both text and image content features, a hybrid image retrieval system for Word Wide Web is developed in this paper. We first use a text-based image meta-search engine to retrieve images from the Web based on the text information on the image host pages to provide an initial image set. Because of the high-speed and low cost nature of the text-based approach, we can easily retrieve a broad coverage of images with a high recall rate and a relatively low precision. An image content based ordering is then performed on the initial image set. All the images are clustered into different folders based on the image content features. In addition, the images can be re-ranked by the content features according to the user feedback. Such a design makes it truly practical to use both text and image content for image retrieval over the Internet. Experimental results confirm the efficiency of the system.

A dose-volume analysis of magnetic resonance imaging-aided high-dose-rate image-based interstitial brachytherapy for uterine cervical cancer.

PubMed

Yoshida, Ken; Yamazaki, Hideya; Takenaka, Tadashi; Kotsuma, Tadayuki; Yoshida, Mineo; Furuya, Seiichi; Tanaka, Eiichi; Uegaki, Tadaaki; Kuriyama, Keiko; Matsumoto, Hisanobu; Yamada, Shigetoshi; Ban, Chiaki

2010-07-01

To investigate the feasibility of our novel image-based high-dose-rate interstitial brachytherapy (HDR-ISBT) for uterine cervical cancer, we evaluated the dose-volume histogram (DVH) according to the recommendations of the Gynecological GEC-ESTRO Working Group for image-based intracavitary brachytherapy (ICBT). Between June 2005 and June 2007, 18 previously untreated cervical cancer patients were enrolled. We implanted magnetic resonance imaging (MRI)-available plastic applicators by our unique ambulatory technique. Total treatment doses were 30-36 Gy (6 Gy per fraction) combined with external beam radiotherapy (EBRT). Treatment plans were created based on planning computed tomography with MRI as a reference. DVHs of the high-risk clinical target volume (HR CTV), intermediate-risk CTV (IR CTV), and the bladder and rectum were calculated. Dose values were biologically normalized to equivalent doses in 2-Gy fractions (EQD(2)). The median D90 (HR CTV) and D90 (IR CTV) per fraction were 6.8 Gy (range, 5.5-7.5) and 5.4 Gy (range, 4.2-6.3), respectively. The median V100 (HR CTV) and V100 (IR CTV) were 98.4% (range, 83-100) and 81.8% (range, 64-93.8), respectively. When the dose of EBRT was added, the median D90 and D100 of HR CTV were 80.6 Gy (range, 65.5-96.6) and 62.4 Gy (range, 49-83.2). The D(2cc) of the bladder was 62 Gy (range, 51.4-89) and of the rectum was 65.9 Gy (range, 48.9-76). Although the targets were advanced and difficult to treat effectively by ICBT, MRI-aided image-based ISBT showed favorable results for CTV and organs at risk compared with previously reported image-based ICBT results. (c) 2010 Elsevier Inc. All rights reserved.

Temperature imaging with speed of ultrasonic transmission tomography for medical treatment control: A physical model-based method

NASA Astrophysics Data System (ADS)

Chu, Zhe-Qi; Yuan, Jie; Stephen, Z. Pinter; Oliver, D. Kripfgans; Wang, Xue-Ding; Paul, L. Carson; Liu, Xiao-Jun

2015-10-01

Hyperthermia is a promising method to enhance chemo and radiation therapy of breast cancer. In the process of hyperthermia, temperature monitoring is of great importance to assure the effectiveness of treatment. The transmission speed of ultrasound in biomedical tissue changes with temperature. However, when mapping the speed of sound directly to temperature in each pixel as desired for using all speeds of ultrasound data, temperature bipolar edge enhancement artifacts occur near the boundary of two tissues with different speeds of ultrasound. After the analysis of the reasons for causing these artifacts, an optimized method is introduced to rebuild the temperature field image by using the continuity constraint as the judgment criterion. The significant smoothness of the rebuilding image in the transitional area shows that our proposed method can build a more precise temperature image for controlling the medical thermal treatment. Project supported in part by DoD/BCRP Idea Award, BC095397P1, the National Natural Science Foundation of China (Grant No. 61201425), the Natural Science Foundation of Jiangsu Province, China (Grant No. BK20131280), the Priority Academic Program Development of Jiangsu Provincial Higher Education Institutions, China, and the National Institutes of Health (NIH) of United States (Grant Nos. R01AR060350, R01CA91713, and R01AR055179).

Stereotactic radiation treatment planning and follow-up studies involving fused multimodality imaging.

PubMed

Hamm, Klaus D; Surber, Gunnar; Schmücking, Michael; Wurm, Reinhard E; Aschenbach, Rene; Kleinert, Gabriele; Niesen, A; Baum, Richard P

2004-11-01

Innovative new software solutions may enable image fusion to produce the desired data superposition for precise target definition and follow-up studies in radiosurgery/stereotactic radiotherapy in patients with intracranial lesions. The aim is to integrate the anatomical and functional information completely into the radiation treatment planning and to achieve an exact comparison for follow-up examinations. Special conditions and advantages of BrainLAB's fully automatic image fusion system are evaluated and described for this purpose. In 458 patients, the radiation treatment planning and some follow-up studies were performed using an automatic image fusion technique involving the use of different imaging modalities. Each fusion was visually checked and corrected as necessary. The computerized tomography (CT) scans for radiation treatment planning (slice thickness 1.25 mm), as well as stereotactic angiography for arteriovenous malformations, were acquired using head fixation with stereotactic arc or, in the case of stereotactic radiotherapy, with a relocatable stereotactic mask. Different magnetic resonance (MR) imaging sequences (T1, T2, and fluid-attenuated inversion-recovery images) and positron emission tomography (PET) scans were obtained without head fixation. Fusion results and the effects on radiation treatment planning and follow-up studies were analyzed. The precision level of the results of the automatic fusion depended primarily on the image quality, especially the slice thickness and the field homogeneity when using MR images, as well as on patient movement during data acquisition. Fully automated image fusion of different MR, CT, and PET studies was performed for each patient. Only in a few cases was it necessary to correct the fusion manually after visual evaluation. These corrections were minor and did not materially affect treatment planning. High-quality fusion of thin slices of a region of interest with a complete head data set could be performed

Rotator Cuff Tear Arthropathy: Pathophysiology, Imaging Characteristics, and Treatment Options.

PubMed

Eajazi, Alireza; Kussman, Steve; LeBedis, Christina; Guermazi, Ali; Kompel, Andrew; Jawa, Andrew; Murakami, Akira M

2015-11-01

The purpose of this article is to review the biomechanical properties of the rotator cuff and glenohumeral joint and the pathophysiology, imaging characteristics, and treatment options of rotator cuff tear arthropathy (RCTA). Although multiple pathways have been proposed as causes of RCTA, the exact cause remains unclear. Increasing knowledge about the clinical diagnosis, imaging features, and indicators of severity improves recognition and treatment of this pathologic condition.

Improving 4D plan quality for PBS-based liver tumour treatments by combining online image guided beam gating with rescanning

NASA Astrophysics Data System (ADS)

Zhang, Ye; Knopf, Antje-Christin; Weber, Damien Charles; Lomax, Antony John

2015-10-01

Pencil beam scanned (PBS) proton therapy has many advantages over conventional radiotherapy, but its effectiveness for treating mobile tumours remains questionable. Gating dose delivery to the breathing pattern is a well-developed method in conventional radiotherapy for mitigating tumour-motion, but its clinical efficiency for PBS proton therapy is not yet well documented. In this study, the dosimetric benefits and the treatment efficiency of beam gating for PBS proton therapy has been comprehensively evaluated. A series of dedicated 4D dose calculations (4DDC) have been performed on 9 different 4DCT(MRI) liver data sets, which give realistic 4DCT extracting motion information from 4DMRI. The value of 4DCT(MRI) is its capability of providing not only patient geometries and deformable breathing characteristics, but also includes variations in the breathing patterns between breathing cycles. In order to monitor target motion and derive a gating signal, we simulate time-resolved beams’ eye view (BEV) x-ray images as an online motion surrogate. 4DDCs have been performed using three amplitude-based gating window sizes (10/5/3 mm) with motion surrogates derived from either pre-implanted fiducial markers or the diaphragm. In addition, gating has also been simulated in combination with up to 19 times rescanning using either volumetric or layered approaches. The quality of the resulting 4DDC plans has been quantified in terms of the plan homogeneity index (HI), total treatment time and duty cycle. Results show that neither beam gating nor rescanning alone can fully retrieve the plan homogeneity of the static reference plan. Especially for variable breathing patterns, reductions of the effective duty cycle to as low as 10% have been observed with the smallest gating rescanning window (3 mm), implying that gating on its own for such cases would result in much longer treatment times. In addition, when rescanning is applied on its own, large differences between volumetric

MO-DE-210-03: Ultrasound imaging is an attractive method for image guided radiation treatment (IGRT), by itself or to complement other imaging modalities

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

Ding, K.

Ultrasound imaging is an attractive method for image guided radiation treatment (IGRT), by itself or to complement other imaging modalities. It is inexpensive, portable and provides good soft tissue contrast. For challenging soft tissue targets such as pancreatic cancer, ultrasound imaging can be used in combination with pre-treatment MRI and/or CT to transfer important anatomical features for target localization at time of treatment. The non-invasive and non-ionizing nature of ultrasound imaging is particularly powerful for intra-fraction localization and monitoring. Recognizing these advantages, efforts are being made to incorporate novel robotic approaches to position and manipulate the ultrasound probe during irradiation.more » These recent enabling developments hold potential to bring ultrasound imaging to a new level of IGRT applications. However, many challenges, not limited to image registration, robotic deployment, probe interference and image acquisition rate, need to be addressed to realize the full potential of IGRT with ultrasound imaging. Learning Objectives: Understand the benefits and limitations in using ultrasound to augment MRI and/or CT for motion monitoring during radiation therapy delivery. Understanding passive and active robotic approaches to implement ultrasound imaging for intra-fraction monitoring. Understand issues of probe interference with radiotherapy treatment. Understand the critical clinical workflow for effective and reproducible IGRT using ultrasound guidance. The work of X.L. is supported in part by Elekta; J.W. and K.D. is supported in part by a NIH grant R01 CA161613 and by Elekta; D.H. is support in part by a NIH grant R41 CA174089.« less

A Study of Patient’s Self-Image during Orthodontic Treatment.

DTIC Science & Technology

1985-06-01

Orthodontic Treatment 4. PERFORMING ORG. REPORT NUMMER 7. AUTHOR(a) U. CONTRACT OR GRANT NUMBER(@) Brian B. Jacobus, Jr. . PERFORMING ORGANIZATION NAME AND...with a correction of the patient’s malocclusion through orthodontic treatment. A study was done to determine what changes occur in the orthodontic ...patient’s self-image dur S ing orthodontic treatment. A questionnaire requiring re- sponses pertaining to self-image was distributed to three hundred

Fast single image dehazing based on image fusion

NASA Astrophysics Data System (ADS)

Liu, Haibo; Yang, Jie; Wu, Zhengping; Zhang, Qingnian

2015-01-01

Images captured in foggy weather conditions often fade the colors and reduce the contrast of the observed objects. An efficient image fusion method is proposed to remove haze from a single input image. First, the initial medium transmission is estimated based on the dark channel prior. Second, the method adopts an assumption that the degradation level affected by haze of each region is the same, which is similar to the Retinex theory, and uses a simple Gaussian filter to get the coarse medium transmission. Then, pixel-level fusion is achieved between the initial medium transmission and coarse medium transmission. The proposed method can recover a high-quality haze-free image based on the physical model, and the complexity of the proposed method is only a linear function of the number of input image pixels. Experimental results demonstrate that the proposed method can allow a very fast implementation and achieve better restoration for visibility and color fidelity compared to some state-of-the-art methods.

SU-E-J-15: Automatically Detect Patient Treatment Position and Orientation in KV Portal Images

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

Qiu, J; Yang, D

2015-06-15

Purpose: In the course of radiation therapy, the complex information processing workflow will Result in potential errors, such as incorrect or inaccurate patient setups. With automatic image check and patient identification, such errors could be effectively reduced. For this purpose, we developed a simple and rapid image processing method, to automatically detect the patient position and orientation in 2D portal images, so to allow automatic check of positions and orientations for patient daily RT treatments. Methods: Based on the principle of portal image formation, a set of whole body DRR images were reconstructed from multiple whole body CT volume datasets,more » and fused together to be used as the matching template. To identify the patient setup position and orientation shown in a 2D portal image, the 2D portal image was preprocessed (contrast enhancement, down-sampling and couch table detection), then matched to the template image so to identify the laterality (left or right), position, orientation and treatment site. Results: Five day’s clinical qualified portal images were gathered randomly, then were processed by the automatic detection and matching method without any additional information. The detection results were visually checked by physicists. 182 images were correct detection in a total of 200kV portal images. The correct rate was 91%. Conclusion: The proposed method can detect patient setup and orientation quickly and automatically. It only requires the image intensity information in KV portal images. This method can be useful in the framework of Electronic Chart Check (ECCK) to reduce the potential errors in workflow of radiation therapy and so to improve patient safety. In addition, the auto-detection results, as the patient treatment site position and patient orientation, could be useful to guide the sequential image processing procedures, e.g. verification of patient daily setup accuracy. This work was partially supported by research grant

Evaluation of port-wine stain treatment outcomes using multispectral imaging

NASA Astrophysics Data System (ADS)

Samatham, Ravikant; Choudhury, Niloy; Krol, Alfons L.; Jacques, Steven L.

2012-02-01

Port-wine Stain (PWS) is a vascular malformation characterized by ectasia of superficial dermal capillaries. The flash-lamp pumped pulsed dye laser (PDL) treatment has been the mainstay of PWS for the last decade. Despite the success of the PDL in significantly fading the PWS, the overall cure rate is less than 10%. The precise efficacy of an individual PDL treatment is hard to evaluate and the treatment outcome is measured by visual observation of clinical fading. A hand-held multi-spectral imaging system was developed to image PWS before and after PDL treatment. In an NIH-funded pilot study multi-spectral camera was used to image PWS in children (2- 17 years). Oxygen saturation (S) and blood content (B) of PWS before and after the treatment was determined by analysis of the reflectance spectra. The outcome of the treatment was evaluated during follow up visits of the patients. One of the major causes of failure of laser therapy of port-wine stains (PWS) is reperfusion of the lesion after laser treatment. Oxygen saturation and blood content maps of PWS before and after treatment can predict regions of reperfusion and subsequent failure of the treatment. The ability to measure reperfusion and to predict lesions or areas susceptible to reperfusion, will help in selection of patients/lesions for laser treatment and help to optimize laser dosimetry for maximum effect. The current studies also should provide a basis for monitoring of future alternative therapies or enhancers of laser treatment in resistant cases.

Enhanced Imaging of Specific Cell-Surface Glycosylation Based on Multi-FRET.

PubMed

Yuan, Baoyin; Chen, Yuanyuan; Sun, Yuqiong; Guo, Qiuping; Huang, Jin; Liu, Jianbo; Meng, Xiangxian; Yang, Xiaohai; Wen, Xiaohong; Li, Zenghui; Li, Lie; Wang, Kemin

2018-05-15

Cell-surface glycosylation contains abundant biological information that reflects cell physiological state, and it is of great value to image cell-surface glycosylation to elucidate its functions. Here we present a hybridization chain reaction (HCR)-based multifluorescence resonance energy transfer (multi-FRET) method for specific imaging of cell-surface glycosylation. By installing donors through metabolic glycan labeling and acceptors through aptamer-tethered nanoassemblies on the same glycoconjugate, intramolecular multi-FRET occurs due to near donor-acceptor distance. Benefiting from amplified effect and spatial flexibility of the HCR nanoassemblies, enhanced multi-FRET imaging of specific cell-surface glycosylation can be obtained. With this HCR-based multi-FRET method, we achieved obvious contrast in imaging of protein-specific GalNAcylation on 7211 cell surfaces. In addition, we demonstrated the general applicability of this method by visualizing the protein-specific sialylation on CEM cell surfaces. Furthermore, the expression changes of CEM cell-surface protein-specific sialylation under drug treatment was accurately monitored. This developed imaging method may provide a powerful tool in researching glycosylation functions, discovering biomarkers, and screening drugs.

Deep Learning MR Imaging-based Attenuation Correction for PET/MR Imaging.

PubMed

Liu, Fang; Jang, Hyungseok; Kijowski, Richard; Bradshaw, Tyler; McMillan, Alan B

2018-02-01

Purpose To develop and evaluate the feasibility of deep learning approaches for magnetic resonance (MR) imaging-based attenuation correction (AC) (termed deep MRAC) in brain positron emission tomography (PET)/MR imaging. Materials and Methods A PET/MR imaging AC pipeline was built by using a deep learning approach to generate pseudo computed tomographic (CT) scans from MR images. A deep convolutional auto-encoder network was trained to identify air, bone, and soft tissue in volumetric head MR images coregistered to CT data for training. A set of 30 retrospective three-dimensional T1-weighted head images was used to train the model, which was then evaluated in 10 patients by comparing the generated pseudo CT scan to an acquired CT scan. A prospective study was carried out for utilizing simultaneous PET/MR imaging for five subjects by using the proposed approach. Analysis of covariance and paired-sample t tests were used for statistical analysis to compare PET reconstruction error with deep MRAC and two existing MR imaging-based AC approaches with CT-based AC. Results Deep MRAC provides an accurate pseudo CT scan with a mean Dice coefficient of 0.971 ± 0.005 for air, 0.936 ± 0.011 for soft tissue, and 0.803 ± 0.021 for bone. Furthermore, deep MRAC provides good PET results, with average errors of less than 1% in most brain regions. Significantly lower PET reconstruction errors were realized with deep MRAC (-0.7% ± 1.1) compared with Dixon-based soft-tissue and air segmentation (-5.8% ± 3.1) and anatomic CT-based template registration (-4.8% ± 2.2). Conclusion The authors developed an automated approach that allows generation of discrete-valued pseudo CT scans (soft tissue, bone, and air) from a single high-spatial-resolution diagnostic-quality three-dimensional MR image and evaluated it in brain PET/MR imaging. This deep learning approach for MR imaging-based AC provided reduced PET reconstruction error relative to a CT-based standard within the brain compared

Uterine fibroids: semiquantitative perfusion MR imaging parameters associated with the intraprocedural and immediate postprocedural treatment efficiencies of MR imaging-guided high-intensity focused ultrasound ablation.

PubMed

Kim, Young-sun; Kim, Byoung-Gie; Rhim, Hyunchul; Bae, Duk-Soo; Lee, Jeong-Won; Kim, Tae-Joong; Choi, Chel Hun; Lee, Yoo-Young; Lim, Hyo Keun

2014-11-01

To determine whether semiquantitative perfusion magnetic resonance (MR) imaging parameters are associated with therapeutic effectiveness of MR imaging-guided high-intensity focused ultrasound ( HIFU high-intensity focused ultrasound ) ablation of uterine fibroids and which semiquantitative perfusion parameters are significant with regard to treatment efficiency. This study was approved by the institutional review board, and informed consent was obtained from all subjects. Seventy-seven women (mean age, 43.3 years) with 119 fibroids (mean diameter, 7.5 cm) treated with MR imaging-guided HIFU high-intensity focused ultrasound ablation were analyzed. The correlation between semiquantitative perfusion MR parameters (peak enhancement, relative peak enhancement, time to peak, wash-in rate, washout rate) and heating and ablation efficiencies (lethal thermal dose volume based on MR thermometry and nonperfused volume based on immediate contrast-enhanced image divided by intended treatment volume) were evaluated by using a linear mixed model on a per-fibroid basis. The specific value of the significant parameter that had a substantial effect on treatment efficiency was determined. The mean peak enhancement, relative peak enhancement, time to peak, wash-in rate, and washout rate of the fibroids were 1293.1 ± 472.8 (range, 570.2-2477.8), 171.4% ± 57.2 (range, 0.6%-370.2%), 137.2 seconds ± 119.8 (range, 20.0-300.0 seconds), 79.5 per second ± 48.2 (range, 12.5-236.7 per second), and 11.4 per second ± 10.1 (range, 0-39.3 per second), respectively. Relative peak enhancement was found to be independently significant for both heating and ablation efficiencies (B = -0.002, P < .001 and B = -0.003, P = .050, respectively). The washout rate was significantly associated with ablation efficiency (B = -0.018, P = .043). Both efficiencies showed the most abrupt transitions at 220% of relative peak enhancement. Relative peak enhancement at semiquantitative perfusion MR imaging was

Implant treatment planning regarding augmentation procedures: panoramic radiographs vs. cone beam computed tomography images.

PubMed

Dagassan-Berndt, Dorothea C; Zitzmann, Nicola U; Walter, Clemens; Schulze, Ralf K W

2016-08-01

To evaluate the impact of cone beam computed tomography (CBCT) imaging on treatment planning regarding augmentation procedures for implant placement. Panoramic radiographs and CBCT images of 40 patients requesting single-tooth implants in 59 sites were retrospectively analyzed by six specialists in implantology, and treatment planning was performed. Therapeutic recommendations were compared with the surgical protocol performed initially. Bone height estimation from panoramic radiographs yielded to higher measures and greater variability compared to CBCT. The suggested treatment plan for lateral and vertical augmentation procedures based on CBCT or panoramic radiographs coincided for 55-72% of the cases. A trend to a more invasive augmentation procedure was seen when planning was based on CBCT. Panoramic radiography revealed 57-63% (lateral) vs. 67% (vertical augmentation) congruent plans in agreement with surgery. Among the dissenting sites, there was a trend toward less invasive planning for lateral augmentation with panoramic radiographs, while vertical augmentation requirements were more frequently more invasive when based on CBCT. Vertical augmentation requirements can be adequately determined from panoramic radiographs. In difficult cases with a deficient lateral alveolar bone, the augmentation schedule may better be evaluated from CBCT to avoid underestimation, which occurs more frequently when based on panoramic radiographs only. However, overall, radiographic interpretation and diagnostic thinking accuracy seem to be mainly depending on the opinion of observers. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Automatic single-image-based rain streaks removal via image decomposition.

PubMed

Kang, Li-Wei; Lin, Chia-Wen; Fu, Yu-Hsiang

2012-04-01

Rain removal from a video is a challenging problem and has been recently investigated extensively. Nevertheless, the problem of rain removal from a single image was rarely studied in the literature, where no temporal information among successive images can be exploited, making the problem very challenging. In this paper, we propose a single-image-based rain removal framework via properly formulating rain removal as an image decomposition problem based on morphological component analysis. Instead of directly applying a conventional image decomposition technique, the proposed method first decomposes an image into the low- and high-frequency (HF) parts using a bilateral filter. The HF part is then decomposed into a "rain component" and a "nonrain component" by performing dictionary learning and sparse coding. As a result, the rain component can be successfully removed from the image while preserving most original image details. Experimental results demonstrate the efficacy of the proposed algorithm.

Web-based tool for visualization of electric field distribution in deep-seated body structures and planning of electroporation-based treatments.

PubMed

Marčan, Marija; Pavliha, Denis; Kos, Bor; Forjanič, Tadeja; Miklavčič, Damijan

2015-01-01

Treatments based on electroporation are a new and promising approach to treating tumors, especially non-resectable ones. The success of the treatment is, however, heavily dependent on coverage of the entire tumor volume with a sufficiently high electric field. Ensuring complete coverage in the case of deep-seated tumors is not trivial and can in best way be ensured by patient-specific treatment planning. The basis of the treatment planning process consists of two complex tasks: medical image segmentation, and numerical modeling and optimization. In addition to previously developed segmentation algorithms for several tissues (human liver, hepatic vessels, bone tissue and canine brain) and the algorithms for numerical modeling and optimization of treatment parameters, we developed a web-based tool to facilitate the translation of the algorithms and their application in the clinic. The developed web-based tool automatically builds a 3D model of the target tissue from the medical images uploaded by the user and then uses this 3D model to optimize treatment parameters. The tool enables the user to validate the results of the automatic segmentation and make corrections if necessary before delivering the final treatment plan. Evaluation of the tool was performed by five independent experts from four different institutions. During the evaluation, we gathered data concerning user experience and measured performance times for different components of the tool. Both user reports and performance times show significant reduction in treatment-planning complexity and time-consumption from 1-2 days to a few hours. The presented web-based tool is intended to facilitate the treatment planning process and reduce the time needed for it. It is crucial for facilitating expansion of electroporation-based treatments in the clinic and ensuring reliable treatment for the patients. The additional value of the tool is the possibility of easy upgrade and integration of modules with new

Layer-Based Approach for Image Pair Fusion.

PubMed

Son, Chang-Hwan; Zhang, Xiao-Ping

2016-04-20

Recently, image pairs, such as noisy and blurred images or infrared and noisy images, have been considered as a solution to provide high-quality photographs under low lighting conditions. In this paper, a new method for decomposing the image pairs into two layers, i.e., the base layer and the detail layer, is proposed for image pair fusion. In the case of infrared and noisy images, simple naive fusion leads to unsatisfactory results due to the discrepancies in brightness and image structures between the image pair. To address this problem, a local contrast-preserving conversion method is first proposed to create a new base layer of the infrared image, which can have visual appearance similar to another base layer such as the denoised noisy image. Then, a new way of designing three types of detail layers from the given noisy and infrared images is presented. To estimate the noise-free and unknown detail layer from the three designed detail layers, the optimization framework is modeled with residual-based sparsity and patch redundancy priors. To better suppress the noise, an iterative approach that updates the detail layer of the noisy image is adopted via a feedback loop. This proposed layer-based method can also be applied to fuse another noisy and blurred image pair. The experimental results show that the proposed method is effective for solving the image pair fusion problem.

A whole-body dual-modality radionuclide optical strategy for preclinical imaging of metastasis and heterogeneous treatment response in different microenvironments.

PubMed

Fruhwirth, Gilbert O; Diocou, Seckou; Blower, Philip J; Ng, Tony; Mullen, Greg E D

2014-04-01

Imaging spontaneous cancer cell metastasis or heterogeneous tumor responses to drug treatment in vivo is difficult to achieve. The goal was to develop a new highly sensitive and reliable preclinical longitudinal in vivo imaging model for this purpose, thereby facilitating discovery and validation of anticancer therapies or molecular imaging agents. The strategy is based on breast cancer cells stably expressing the human sodium iodide symporter (NIS) fused to a red fluorescent protein, thereby permitting radionuclide and fluorescence imaging. Using whole-body nano-SPECT/CT with (99m)TcO4(-), we followed primary tumor growth and spontaneous metastasis in the presence or absence of etoposide treatment. NIS imaging was used to classify organs as small as individual lymph nodes (LNs) to be positive or negative for metastasis, and results were confirmed by confocal fluorescence microscopy. Etoposide treatment efficacy was proven by ex vivo anticaspase 3 staining and fluorescence microscopy. In this preclinical model, we found that the NIS imaging strategy outperformed state-of-the-art (18)F-FDG imaging in its ability to detect small tumors (18.5-fold-better tumor-to-blood ratio) and metastases (LN, 3.6-fold) because of improved contrast in organs close to metastatic sites (12- and 8.5-fold-lower standardized uptake value in the heart and kidney, respectively). We applied the model to assess the treatment response to the neoadjuvant etoposide and found a consistent and reliable improvement in spontaneous metastasis detection. Importantly, we also found that tumor cells in different microenvironments responded in a heterogeneous manner to etoposide treatment, which could be determined only by the NIS-based strategy and not by (18)F-FDG imaging. We developed a new strategy for preclinical longitudinal in vivo cancer cell tracking with greater sensitivity and reliability than (18)F-FDG PET and applied it to track spontaneous and distant metastasis in the presence or absence

Patch-based image reconstruction for PET using prior-image derived dictionaries

NASA Astrophysics Data System (ADS)

Tahaei, Marzieh S.; Reader, Andrew J.

2016-09-01

In PET image reconstruction, regularization is often needed to reduce the noise in the resulting images. Patch-based image processing techniques have recently been successfully used for regularization in medical image reconstruction through a penalized likelihood framework. Re-parameterization within reconstruction is another powerful regularization technique in which the object in the scanner is re-parameterized using coefficients for spatially-extensive basis vectors. In this work, a method for extracting patch-based basis vectors from the subject’s MR image is proposed. The coefficients for these basis vectors are then estimated using the conventional MLEM algorithm. Furthermore, using the alternating direction method of multipliers, an algorithm for optimizing the Poisson log-likelihood while imposing sparsity on the parameters is also proposed. This novel method is then utilized to find sparse coefficients for the patch-based basis vectors extracted from the MR image. The results indicate the superiority of the proposed methods to patch-based regularization using the penalized likelihood framework.

Automated bone segmentation from dental CBCT images using patch-based sparse representation and convex optimization

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

Wang, Li; Gao, Yaozong; Shi, Feng

Purpose: Cone-beam computed tomography (CBCT) is an increasingly utilized imaging modality for the diagnosis and treatment planning of the patients with craniomaxillofacial (CMF) deformities. Accurate segmentation of CBCT image is an essential step to generate three-dimensional (3D) models for the diagnosis and treatment planning of the patients with CMF deformities. However, due to the poor image quality, including very low signal-to-noise ratio and the widespread image artifacts such as noise, beam hardening, and inhomogeneity, it is challenging to segment the CBCT images. In this paper, the authors present a new automatic segmentation method to address these problems. Methods: To segmentmore » CBCT images, the authors propose a new method for fully automated CBCT segmentation by using patch-based sparse representation to (1) segment bony structures from the soft tissues and (2) further separate the mandible from the maxilla. Specifically, a region-specific registration strategy is first proposed to warp all the atlases to the current testing subject and then a sparse-based label propagation strategy is employed to estimate a patient-specific atlas from all aligned atlases. Finally, the patient-specific atlas is integrated into amaximum a posteriori probability-based convex segmentation framework for accurate segmentation. Results: The proposed method has been evaluated on a dataset with 15 CBCT images. The effectiveness of the proposed region-specific registration strategy and patient-specific atlas has been validated by comparing with the traditional registration strategy and population-based atlas. The experimental results show that the proposed method achieves the best segmentation accuracy by comparison with other state-of-the-art segmentation methods. Conclusions: The authors have proposed a new CBCT segmentation method by using patch-based sparse representation and convex optimization, which can achieve considerably accurate segmentation results in CBCT

Personalized, relevance-based Multimodal Robotic Imaging and augmented reality for Computer Assisted Interventions.

PubMed

Navab, Nassir; Fellow, Miccai; Hennersperger, Christoph; Frisch, Benjamin; Fürst, Bernhard

2016-10-01

In the last decade, many researchers in medical image computing and computer assisted interventions across the world focused on the development of the Virtual Physiological Human (VPH), aiming at changing the practice of medicine from classification and treatment of diseases to that of modeling and treating patients. These projects resulted in major advancements in segmentation, registration, morphological, physiological and biomechanical modeling based on state of art medical imaging as well as other sensory data. However, a major issue which has not yet come into the focus is personalizing intra-operative imaging, allowing for optimal treatment. In this paper, we discuss the personalization of imaging and visualization process with particular focus on satisfying the challenging requirements of computer assisted interventions. We discuss such requirements and review a series of scientific contributions made by our research team to tackle some of these major challenges. Copyright © 2016. Published by Elsevier B.V.

An initial study on the estimation of time-varying volumetric treatment images and 3D tumor localization from single MV cine EPID images

PubMed Central

Mishra, Pankaj; Li, Ruijiang; Mak, Raymond H.; Rottmann, Joerg; Bryant, Jonathan H.; Williams, Christopher L.; Berbeco, Ross I.; Lewis, John H.

2014-01-01

Purpose: In this work the authors develop and investigate the feasibility of a method to estimate time-varying volumetric images from individual MV cine electronic portal image device (EPID) images. Methods: The authors adopt a two-step approach to time-varying volumetric image estimation from a single cine EPID image. In the first step, a patient-specific motion model is constructed from 4DCT. In the second step, parameters in the motion model are tuned according to the information in the EPID image. The patient-specific motion model is based on a compact representation of lung motion represented in displacement vector fields (DVFs). DVFs are calculated through deformable image registration (DIR) of a reference 4DCT phase image (typically peak-exhale) to a set of 4DCT images corresponding to different phases of a breathing cycle. The salient characteristics in the DVFs are captured in a compact representation through principal component analysis (PCA). PCA decouples the spatial and temporal components of the DVFs. Spatial information is represented in eigenvectors and the temporal information is represented by eigen-coefficients. To generate a new volumetric image, the eigen-coefficients are updated via cost function optimization based on digitally reconstructed radiographs and projection images. The updated eigen-coefficients are then multiplied with the eigenvectors to obtain updated DVFs that, in turn, give the volumetric image corresponding to the cine EPID image. Results: The algorithm was tested on (1) Eight digital eXtended CArdiac-Torso phantom datasets based on different irregular patient breathing patterns and (2) patient cine EPID images acquired during SBRT treatments. The root-mean-squared tumor localization error is (0.73 ± 0.63 mm) for the XCAT data and (0.90 ± 0.65 mm) for the patient data. Conclusions: The authors introduced a novel method of estimating volumetric time-varying images from single cine EPID images and a PCA-based lung motion model

An initial study on the estimation of time-varying volumetric treatment images and 3D tumor localization from single MV cine EPID images

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

Mishra, Pankaj, E-mail: pankaj.mishra@varian.com; Mak, Raymond H.; Rottmann, Joerg

2014-08-15

Purpose: In this work the authors develop and investigate the feasibility of a method to estimate time-varying volumetric images from individual MV cine electronic portal image device (EPID) images. Methods: The authors adopt a two-step approach to time-varying volumetric image estimation from a single cine EPID image. In the first step, a patient-specific motion model is constructed from 4DCT. In the second step, parameters in the motion model are tuned according to the information in the EPID image. The patient-specific motion model is based on a compact representation of lung motion represented in displacement vector fields (DVFs). DVFs are calculatedmore » through deformable image registration (DIR) of a reference 4DCT phase image (typically peak-exhale) to a set of 4DCT images corresponding to different phases of a breathing cycle. The salient characteristics in the DVFs are captured in a compact representation through principal component analysis (PCA). PCA decouples the spatial and temporal components of the DVFs. Spatial information is represented in eigenvectors and the temporal information is represented by eigen-coefficients. To generate a new volumetric image, the eigen-coefficients are updated via cost function optimization based on digitally reconstructed radiographs and projection images. The updated eigen-coefficients are then multiplied with the eigenvectors to obtain updated DVFs that, in turn, give the volumetric image corresponding to the cine EPID image. Results: The algorithm was tested on (1) Eight digital eXtended CArdiac-Torso phantom datasets based on different irregular patient breathing patterns and (2) patient cine EPID images acquired during SBRT treatments. The root-mean-squared tumor localization error is (0.73 ± 0.63 mm) for the XCAT data and (0.90 ± 0.65 mm) for the patient data. Conclusions: The authors introduced a novel method of estimating volumetric time-varying images from single cine EPID images and a PCA-based lung

PET/CT imaging for treatment verification after proton therapy: A study with plastic phantoms and metallic implants

PubMed Central

Parodi, Katia; Paganetti, Harald; Cascio, Ethan; Flanz, Jacob B.; Bonab, Ali A.; Alpert, Nathaniel M.; Lohmann, Kevin; Bortfeld, Thomas

2008-01-01

The feasibility of off-line positron emission tomography/computed tomography (PET/CT) for routine three dimensional in-vivo treatment verification of proton radiation therapy is currently under investigation at Massachusetts General Hospital in Boston. In preparation for clinical trials, phantom experiments were carried out to investigate the sensitivity and accuracy of the method depending on irradiation and imaging parameters. Furthermore, they addressed the feasibility of PET/CT as a robust verification tool in the presence of metallic implants. These produce x-ray CT artifacts and fluence perturbations which may compromise the accuracy of treatment planning algorithms. Spread-out Bragg peak proton fields were delivered to different phantoms consisting of polymethylmethacrylate (PMMA), PMMA stacked with lung and bone equivalent materials, and PMMA with titanium rods to mimic implants in patients. PET data were acquired in list mode starting within 20 min after irradiation at a commercial luthetium-oxyorthosilicate (LSO)-based PET/CT scanner. The amount and spatial distribution of the measured activity could be well reproduced by calculations based on the GEANT4 and FLUKA Monte Carlo codes. This phantom study supports the potential of millimeter accuracy for range monitoring and lateral field position verification even after low therapeutic dose exposures of 2 Gy, despite the delay between irradiation and imaging. It also indicates the value of PET for treatment verification in the presence of metallic implants, demonstrating a higher sensitivity to fluence perturbations in comparison to a commercial analytical treatment planning system. Finally, it addresses the suitability of LSO-based PET detectors for hadron therapy monitoring. This unconventional application of PET involves countrates which are orders of magnitude lower than in diagnostic tracer imaging, i.e., the signal of interest is comparable to the noise originating from the intrinsic radioactivity of

Nanoparticle-enabled, image-guided treatment planning of target specific RNAi therapeutics in an orthotopic prostate cancer model.

PubMed

Lin, Qiaoya; Jin, Cheng S; Huang, Huang; Ding, Lili; Zhang, Zhihong; Chen, Juan; Zheng, Gang

2014-08-13

The abilities to deliver siRNA to its intended action site and assess the delivery efficiency are challenges for current RNAi therapy, where effective siRNA delivery will join force with patient genetic profiling to achieve optimal treatment outcome. Imaging could become a critical enabler to maximize RNAi efficacy in the context of tracking siRNA delivery, rational dosimetry and treatment planning. Several imaging modalities have been used to visualize nanoparticle-based siRNA delivery but rarely did they guide treatment planning. We report a multimodal theranostic lipid-nanoparticle, HPPS(NIR)-chol-siRNA, which has a near-infrared (NIR) fluorescent core, enveloped by phospholipid monolayer, intercalated with siRNA payloads, and constrained by apoA-I mimetic peptides to give ultra-small particle size (<30 nm). Using fluorescence imaging, we demonstrated its cytosolic delivery capability for both NIR-core and dye-labeled siRNAs and its structural integrity in mice through intravenous administration, validating the usefulness of NIR-core as imaging surrogate for non-labeled therapeutic siRNAs. Next, we validated the targeting specificity of HPPS(NIR)-chol-siRNA to orthotopic tumor using sequential four-steps (in vivo, in situ, ex vivo and frozen-tissue) fluorescence imaging. The image co-registration of computed tomography and fluorescence molecular tomography enabled non-invasive assessment and treatment planning of siRNA delivery into the orthotopic tumor, achieving efficacious RNAi therapy. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Image segmentation-based robust feature extraction for color image watermarking

NASA Astrophysics Data System (ADS)

Li, Mianjie; Deng, Zeyu; Yuan, Xiaochen

2018-04-01

This paper proposes a local digital image watermarking method based on Robust Feature Extraction. The segmentation is achieved by Simple Linear Iterative Clustering (SLIC) based on which an Image Segmentation-based Robust Feature Extraction (ISRFE) method is proposed for feature extraction. Our method can adaptively extract feature regions from the blocks segmented by SLIC. This novel method can extract the most robust feature region in every segmented image. Each feature region is decomposed into low-frequency domain and high-frequency domain by Discrete Cosine Transform (DCT). Watermark images are then embedded into the coefficients in the low-frequency domain. The Distortion-Compensated Dither Modulation (DC-DM) algorithm is chosen as the quantization method for embedding. The experimental results indicate that the method has good performance under various attacks. Furthermore, the proposed method can obtain a trade-off between high robustness and good image quality.

Space-based optical image encryption.

PubMed

Chen, Wen; Chen, Xudong

2010-12-20

In this paper, we propose a new method based on a three-dimensional (3D) space-based strategy for the optical image encryption. The two-dimensional (2D) processing of a plaintext in the conventional optical encryption methods is extended to a 3D space-based processing. Each pixel of the plaintext is considered as one particle in the proposed space-based optical image encryption, and the diffraction of all particles forms an object wave in the phase-shifting digital holography. The effectiveness and advantages of the proposed method are demonstrated by numerical results. The proposed method can provide a new optical encryption strategy instead of the conventional 2D processing, and may open up a new research perspective for the optical image encryption.

Nuclear emission-based imaging in the study of brain function

NASA Astrophysics Data System (ADS)

Sossi, Vesna

2016-09-01

Nuclear emission - based imaging has been used in medicine for decades either in the form of Single Photon Emission Computerized Tomography (SPECT) or Positron Emission Tomography (PET). Both techniques are based on radiolabelling molecules of biological interest (radiotracers) with either a gamma (SPECT) or a positron (PET) emitting radionuclide. By detecting radiation from the radiolabels and reconstructing the acquired data it is possible to form an image of the radiotracer distribution in the body and thus obtain information on the biological process that the radiotracer is tagging. While most of the clinical applications of PET are in oncology, where the glucose analogue 18F-flurodeoxyglocose (FDG) is the most commonly used radiotracer, the importance of PET imaging for brain applications is rapidly increasing. Numerous radiotracers exist that can tag different neurotransmitter systems as well as abnormal protein aggregations that are known to underlie several brain diseases: amyloid deposition, a characteristic of Alzheimer's, and, more recently, tau deposition, which is deemed abnormal not only in dementia, but also in Parkinson's syndrome and traumatic brain injury. Imaging has shown that may brain diseases start decades before clinical symptoms, in part explaining the difficulty of developing adequate treatments. This talk will briefly summarize the role of PET imaging in the study of neurodegeneration and discuss the upcoming hybrid PET/MRI imaging instrumentation. NSERC, CIHR, MJFF.

Global image analysis to determine suitability for text-based image personalization

NASA Astrophysics Data System (ADS)

Ding, Hengzhou; Bala, Raja; Fan, Zhigang; Bouman, Charles A.; Allebach, Jan P.

2012-03-01

Lately, image personalization is becoming an interesting topic. Images with variable elements such as text usually appear much more appealing to the recipients. In this paper, we describe a method to pre-analyze the image and automatically suggest to the user the most suitable regions within an image for text-based personalization. The method is based on input gathered from experiments conducted with professional designers. It has been observed that regions that are spatially smooth and regions with existing text (e.g. signage, banners, etc.) are the best candidates for personalization. This gives rise to two sets of corresponding algorithms: one for identifying smooth areas, and one for locating text regions. Furthermore, based on the smooth and text regions found in the image, we derive an overall metric to rate the image in terms of its suitability for personalization (SFP).

Algorithm for lung cancer detection based on PET/CT images

NASA Astrophysics Data System (ADS)

Saita, Shinsuke; Ishimatsu, Keita; Kubo, Mitsuru; Kawata, Yoshiki; Niki, Noboru; Ohtsuka, Hideki; Nishitani, Hiromu; Ohmatsu, Hironobu; Eguchi, Kenji; Kaneko, Masahiro; Moriyama, Noriyuki

2009-02-01

The five year survival rate of the lung cancer is low with about twenty-five percent. In addition it is an obstinate lung cancer wherein three out of four people die within five years. Then, the early stage detection and treatment of the lung cancer are important. Recently, we can obtain CT and PET image at the same time because PET/CT device has been developed. PET/CT is possible for a highly accurate cancer diagnosis because it analyzes quantitative shape information from CT image and FDG distribution from PET image. However, neither benign-malignant classification nor staging intended for lung cancer have been established still enough by using PET/CT images. In this study, we detect lung nodules based on internal organs extracted from CT image, and we also develop algorithm which classifies benignmalignant and metastatic or non metastatic lung cancer using lung structure and FDG distribution(one and two hour after administering FDG). We apply the algorithm to 59 PET/CT images (malignant 43 cases [Ad:31, Sq:9, sm:3], benign 16 cases) and show the effectiveness of this algorithm.

The research on medical image classification algorithm based on PLSA-BOW model.

PubMed

Cao, C H; Cao, H L

2016-04-29

With the rapid development of modern medical imaging technology, medical image classification has become more important for medical diagnosis and treatment. To solve the existence of polysemous words and synonyms problem, this study combines the word bag model with PLSA (Probabilistic Latent Semantic Analysis) and proposes the PLSA-BOW (Probabilistic Latent Semantic Analysis-Bag of Words) model. In this paper we introduce the bag of words model in text field to image field, and build the model of visual bag of words model. The method enables the word bag model-based classification method to be further improved in accuracy. The experimental results show that the PLSA-BOW model for medical image classification can lead to a more accurate classification.

Retinal image quality assessment based on image clarity and content

NASA Astrophysics Data System (ADS)

Abdel-Hamid, Lamiaa; El-Rafei, Ahmed; El-Ramly, Salwa; Michelson, Georg; Hornegger, Joachim

2016-09-01

Retinal image quality assessment (RIQA) is an essential step in automated screening systems to avoid misdiagnosis caused by processing poor quality retinal images. A no-reference transform-based RIQA algorithm is introduced that assesses images based on five clarity and content quality issues: sharpness, illumination, homogeneity, field definition, and content. Transform-based RIQA algorithms have the advantage of considering retinal structures while being computationally inexpensive. Wavelet-based features are proposed to evaluate the sharpness and overall illumination of the images. A retinal saturation channel is designed and used along with wavelet-based features for homogeneity assessment. The presented sharpness and illumination features are utilized to assure adequate field definition, whereas color information is used to exclude nonretinal images. Several publicly available datasets of varying quality grades are utilized to evaluate the feature sets resulting in area under the receiver operating characteristic curve above 0.99 for each of the individual feature sets. The overall quality is assessed by a classifier that uses the collective features as an input vector. The classification results show superior performance of the algorithm in comparison to other methods from literature. Moreover, the algorithm addresses efficiently and comprehensively various quality issues and is suitable for automatic screening systems.

Peripheral vascular tumors and vascular malformations: imaging (magnetic resonance imaging and conventional angiography), pathologic correlation and treatment options.

PubMed

El-Merhi, Fadi; Garg, Deepak; Cura, Marco; Ghaith, Ola

2013-02-01

Vascular anomalies are classified into vascular tumors (infantile hemangioma) and vascular malformations. Vascular malformations are divided into slow flow and high flow subtypes. Magnetic resonance imaging helps in classification and assessing extent and distribution. Conventional angiography also known as digital subtraction angiography is pivotal in assessment of fine vascular details and treatment planning. Imaging correlates well with histopathology. We review recent development in imaging techniques of various vascular anomalies most of which are affecting the peripheral system which potentially may broaden understanding of their diagnosis, classification and treatment.

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

Cloud-based image sharing network for collaborative imaging diagnosis and consultation

NASA Astrophysics Data System (ADS)

Yang, Yuanyuan; Gu, Yiping; Wang, Mingqing; Sun, Jianyong; Li, Ming; Zhang, Weiqiang; Zhang, Jianguo

2018-03-01

In this presentation, we presented a new approach to design cloud-based image sharing network for collaborative imaging diagnosis and consultation through Internet, which can enable radiologists, specialists and physicians locating in different sites collaboratively and interactively to do imaging diagnosis or consultation for difficult or emergency cases. The designed network combined a regional RIS, grid-based image distribution management, an integrated video conferencing system and multi-platform interactive image display devices together with secured messaging and data communication. There are three kinds of components in the network: edge server, grid-based imaging documents registry and repository, and multi-platform display devices. This network has been deployed in a public cloud platform of Alibaba through Internet since March 2017 and used for small lung nodule or early staging lung cancer diagnosis services between Radiology departments of Huadong hospital in Shanghai and the First Hospital of Jiaxing in Zhejiang Province.

Taxonomy of multi-focal nematode image stacks by a CNN based image fusion approach.

PubMed

Liu, Min; Wang, Xueping; Zhang, Hongzhong

2018-03-01

In the biomedical field, digital multi-focal images are very important for documentation and communication of specimen data, because the morphological information for a transparent specimen can be captured in form of a stack of high-quality images. Given biomedical image stacks containing multi-focal images, how to efficiently extract effective features from all layers to classify the image stacks is still an open question. We present to use a deep convolutional neural network (CNN) image fusion based multilinear approach for the taxonomy of multi-focal image stacks. A deep CNN based image fusion technique is used to combine relevant information of multi-focal images within a given image stack into a single image, which is more informative and complete than any single image in the given stack. Besides, multi-focal images within a stack are fused along 3 orthogonal directions, and multiple features extracted from the fused images along different directions are combined by canonical correlation analysis (CCA). Because multi-focal image stacks represent the effect of different factors - texture, shape, different instances within the same class and different classes of objects, we embed the deep CNN based image fusion method within a multilinear framework to propose an image fusion based multilinear classifier. The experimental results on nematode multi-focal image stacks demonstrated that the deep CNN image fusion based multilinear classifier can reach a higher classification rate (95.7%) than that by the previous multilinear based approach (88.7%), even we only use the texture feature instead of the combination of texture and shape features as in the previous work. The proposed deep CNN image fusion based multilinear approach shows great potential in building an automated nematode taxonomy system for nematologists. It is effective to classify multi-focal image stacks. Copyright © 2018 Elsevier B.V. All rights reserved.

WE-A-BRD-01: MR Imaging for Treatment Planning: What Every Physicist Should Know

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

McGee, K.

2015-06-15

Ever since its introduction as a diagnostic imaging modality over 30 years ago, the radiation therapy community has acknowledged the utility of MR imaging as a tool for not only improved visualization of the target volume but also for demarcation of adjacent organs at risk. However, the adaptation of MR imaging in radiation oncology has, until recently been slow due in large part to the inability to image radiation therapy patients in their treatment position. With the introduction of so-called wide bore high field MR scanners, multi element flexible receive only RF coils, high performance imaging gradients and a rangemore » of volumetric imaging sequences it is now possible to obtain both high resolution and high signal-to-noise ratio images of in-treatment radiation therapy patients within clinically feasible imaging times. As a Result, there is renewed interest in the use of MR imaging for radiation oncology treatment planning that is being translated into physical siting and integration of these systems into radiation oncology departments. As MR imaging expands into the radiation oncology domain there is a significant and unmet need for radiation therapy physicists to become educated regarding the strengths, limitations and technical challenges associated with MR imaging. The purpose of this presentation is to address this need by providing an educational overview of the techniques and challenges associated with MR imaging of patients for radiation therapy treatment planning. As such this presentation will: 1) describe the fundamental differences between imaging of patients for diagnostic and therapeutic purposes (i.e. radiation therapy planning), 2) describe most commonly used imaging sequences and contrasts for identification of disease for radiation planning, 3) identify the most common sources of image distortion and techniques to reduce their effect on spatial fidelity of the MR data, 4) describe the effects of motion and methods to quantify/correct it

Content-based image retrieval on mobile devices

NASA Astrophysics Data System (ADS)

Ahmad, Iftikhar; Abdullah, Shafaq; Kiranyaz, Serkan; Gabbouj, Moncef

2005-03-01

Content-based image retrieval area possesses a tremendous potential for exploration and utilization equally for researchers and people in industry due to its promising results. Expeditious retrieval of desired images requires indexing of the content in large-scale databases along with extraction of low-level features based on the content of these images. With the recent advances in wireless communication technology and availability of multimedia capable phones it has become vital to enable query operation in image databases and retrieve results based on the image content. In this paper we present a content-based image retrieval system for mobile platforms, providing the capability of content-based query to any mobile device that supports Java platform. The system consists of light-weight client application running on a Java enabled device and a server containing a servlet running inside a Java enabled web server. The server responds to image query using efficient native code from selected image database. The client application, running on a mobile phone, is able to initiate a query request, which is handled by a servlet in the server for finding closest match to the queried image. The retrieved results are transmitted over mobile network and images are displayed on the mobile phone. We conclude that such system serves as a basis of content-based information retrieval on wireless devices and needs to cope up with factors such as constraints on hand-held devices and reduced network bandwidth available in mobile environments.

Evaluation method based on the image correlation for laser jamming image

NASA Astrophysics Data System (ADS)

Che, Jinxi; Li, Zhongmin; Gao, Bo

2013-09-01

The jamming effectiveness evaluation of infrared imaging system is an important part of electro-optical countermeasure. The infrared imaging devices in the military are widely used in the searching, tracking and guidance and so many other fields. At the same time, with the continuous development of laser technology, research of laser interference and damage effect developed continuously, laser has been used to disturbing the infrared imaging device. Therefore, the effect evaluation of the infrared imaging system by laser has become a meaningful problem to be solved. The information that the infrared imaging system ultimately present to the user is an image, so the evaluation on jamming effect can be made from the point of assessment of image quality. The image contains two aspects of the information, the light amplitude and light phase, so the image correlation can accurately perform the difference between the original image and disturbed image. In the paper, the evaluation method of digital image correlation, the assessment method of image quality based on Fourier transform, the estimate method of image quality based on error statistic and the evaluation method of based on peak signal noise ratio are analysed. In addition, the advantages and disadvantages of these methods are analysed. Moreover, the infrared disturbing images of the experiment result, in which the thermal infrared imager was interfered by laser, were analysed by using these methods. The results show that the methods can better reflect the jamming effects of the infrared imaging system by laser. Furthermore, there is good consistence between evaluation results by using the methods and the results of subjective visual evaluation. And it also provides well repeatability and convenient quantitative analysis. The feasibility of the methods to evaluate the jamming effect was proved. It has some extent reference value for the studying and developing on electro-optical countermeasures equipments and

Tc-99m imaging in thyroidectomized differentiated thyroid cancer patients immediately before I-131 treatment.

PubMed

Tsai, Chi-Jung; Cheng, Cheng-Yi; Shen, Daniel Hueng-Yuan; Kuo, Shou Jen; Wang, Lien-Yen; Lee, Chiang-Hsuan; Wang, Jhi-Joung; Chang, Ming-Che; Huang, Wen-Sheng

2016-02-01

The aim of this study was to evaluate the clinical role of technetium-99m pertechnetate (Tc-99m) imaging in thyroidectomized differentiated thyroid cancer patients immediately before radioiodine-131 (I-131) treatment (Tx). Eighty-six consecutive post-total-thyroidectomy patients (15 men, 71 women; mean age: 46.8 years) with pathologically diagnosed differentiated thyroid cancer were retrospectively studied. Tc-99m imaging immediately before I-131 Tx using both patient-based and lesion-based measurements were analyzed and were further compared with those of post-Tx I-131 whole-body scans. For patients with unequivocally positive Tc-99m uptake, the sensitivity was 77% (patient-based) and 59% (site-based). The positive predictive value (PPV) was 100% for both patient-based and site-based measurements. If equivocal Tc-99m uptake was counted as positive, the sensitivity was 83 and 67%, and the PPV was 100 and 99% for patient-based and site-based measurements, respectively. (a) To increase sensitivity yet maintaining high PPV, equivocal Tc-99m uptake should be considered a positive finding. (b) The nearly 100% PPV of Tc-99m imaging immediately before I-131 Tx for remnant detection suggests that Tc-99m imaging not only serves as an alternative to low-dose I-131 scanning in the low-risk post-thyroidectomy patients but also provides a clue for the subsequent I-131 therapeutic dosage and even for the outcome prediction.

Ontology-based malaria parasite stage and species identification from peripheral blood smear images.

PubMed

Makkapati, Vishnu V; Rao, Raghuveer M

2011-01-01

The diagnosis and treatment of malaria infection requires detecting the presence of the malaria parasite in the patient as well as identification of the parasite species. We present an image processing-based approach to detect parasites in microscope images of a blood smear and an ontology-based classification of the stage of the parasite for identifying the species of infection. This approach is patterned after the diagnosis approach adopted by a pathologist for visual examination, and hence, is expected to deliver similar results. We formulate several rules based on the morphology of the basic components of a parasite, namely, chromatin dot(s) and cytoplasm, to identify the parasite stage and species. Numerical results are presented for data taken from various patients. A sensitivity of 88% and a specificity of 95% is reported by evaluation of the scheme on 55 images.

Planning of electroporation-based treatments using Web-based treatment-planning software.

PubMed

Pavliha, Denis; Kos, Bor; Marčan, Marija; Zupanič, Anže; Serša, Gregor; Miklavčič, Damijan

2013-11-01

Electroporation-based treatment combining high-voltage electric pulses and poorly permanent cytotoxic drugs, i.e., electrochemotherapy (ECT), is currently used for treating superficial tumor nodules by following standard operating procedures. Besides ECT, another electroporation-based treatment, nonthermal irreversible electroporation (N-TIRE), is also efficient at ablating deep-seated tumors. To perform ECT or N-TIRE of deep-seated tumors, following standard operating procedures is not sufficient and patient-specific treatment planning is required for successful treatment. Treatment planning is required because of the use of individual long-needle electrodes and the diverse shape, size and location of deep-seated tumors. Many institutions that already perform ECT of superficial metastases could benefit from treatment-planning software that would enable the preparation of patient-specific treatment plans. To this end, we have developed a Web-based treatment-planning software for planning electroporation-based treatments that does not require prior engineering knowledge from the user (e.g., the clinician). The software includes algorithms for automatic tissue segmentation and, after segmentation, generation of a 3D model of the tissue. The procedure allows the user to define how the electrodes will be inserted. Finally, electric field distribution is computed, the position of electrodes and the voltage to be applied are optimized using the 3D model and a downloadable treatment plan is made available to the user.

Slipped upper femoral epiphysis: imaging of complications after treatment.

PubMed

Tins, B; Cassar-Pullicino, V; McCall, I

2008-01-01

Slipped upper femoral epiphysis (SUFE) is a multifactorial condition usually affecting adolescents. Obesity is one risk factor, and as this is increasing the incidence of SUFE is likely to rise. Diagnosis and treatment are usually straightforward and carried out by orthopaedic surgeons. However, the recognition of post-treatment complications poses a much greater challenge. This article focuses on possible complications of surgical treatment of SUFE particularly. Chondrolysis, avascular necrosis, as well as other complications of treatment and conditions leading to premature osteoarthritis are discussed. Checklists for a systematic approach to post-treatment imaging are provided.

SU-E-J-13: A Study to Establish the Effect of CBCT Image Rotational Displacement on IGRT and ART Lung SBRT Treatments.

PubMed

Yeager, C; Lin, H; Ayan, A; McDonough, J; Both, S

2012-06-01

To determine whether the accuracy of CBCT based IGRT and ART lung SBRT treatments may require extra quality assurance (QA) steps. During CBCT Rando phantom acquisition we detected an unexpected ∼2° image rotation when comparing the CW and CCW acquired scans. Misregistered angular coordinates may Result in a rotated reconstructed image and the target localization may lead to an under- or over-dosage of the target volume (TV) and organs at risk (OARs). The effect of image rotation on CBCT-guided lung SBRT was retrospectively examined in a group of six patients treated at our institution. Patient CT sets were rotated by 1,2, and 3°. Treatment plans were recalculated using these rotated images to examine changes of dose-volume histogram indicators for IGRT and ART guided treatments. C++ simulations were run to evaluate the effect of CBCT image rotation. We determined through mathematical analysis that the dose coverage of the TV is dependent on its shape, location and orientation relative to isocenter. Dosimetric evaluation of lung SBRT patients showed that even for 1< Ñ 2 <3°, changes in D95 to the PTV were from 2.3 ± 2.1 to 11.5 ± 3.9% for IGRT and from 8.5 ± 8.4 to 16.6 ± 8.0% for ART. Significant changes were also detected at critical structure level. When IGRT and ART are employed for lung SBRT treatments, significant dosimetric changes may Result from the rotation of CBCT image data sets. The extent of alterations in dose indicators depends on both the shape of the TV and its relative location to isocenter. Based on our results, angular alignment of CBCT to <1° is essential in maintaining accurate dose delivery of IGRT and ART based lung SBRT treatments. © 2012 American Association of Physicists in Medicine.

Image based performance analysis of thermal imagers

NASA Astrophysics Data System (ADS)

Wegner, D.; Repasi, E.

2016-05-01

Due to advances in technology, modern thermal imagers resemble sophisticated image processing systems in functionality. Advanced signal and image processing tools enclosed into the camera body extend the basic image capturing capability of thermal cameras. This happens in order to enhance the display presentation of the captured scene or specific scene details. Usually, the implemented methods are proprietary company expertise, distributed without extensive documentation. This makes the comparison of thermal imagers especially from different companies a difficult task (or at least a very time consuming/expensive task - e.g. requiring the execution of a field trial and/or an observer trial). For example, a thermal camera equipped with turbulence mitigation capability stands for such a closed system. The Fraunhofer IOSB has started to build up a system for testing thermal imagers by image based methods in the lab environment. This will extend our capability of measuring the classical IR-system parameters (e.g. MTF, MTDP, etc.) in the lab. The system is set up around the IR- scene projector, which is necessary for the thermal display (projection) of an image sequence for the IR-camera under test. The same set of thermal test sequences might be presented to every unit under test. For turbulence mitigation tests, this could be e.g. the same turbulence sequence. During system tests, gradual variation of input parameters (e. g. thermal contrast) can be applied. First ideas of test scenes selection and how to assembly an imaging suite (a set of image sequences) for the analysis of imaging thermal systems containing such black boxes in the image forming path is discussed.

Optical image hiding based on computational ghost imaging

NASA Astrophysics Data System (ADS)

Wang, Le; Zhao, Shengmei; Cheng, Weiwen; Gong, Longyan; Chen, Hanwu

2016-05-01

Imaging hiding schemes play important roles in now big data times. They provide copyright protections of digital images. In the paper, we propose a novel image hiding scheme based on computational ghost imaging to have strong robustness and high security. The watermark is encrypted with the configuration of a computational ghost imaging system, and the random speckle patterns compose a secret key. Least significant bit algorithm is adopted to embed the watermark and both the second-order correlation algorithm and the compressed sensing (CS) algorithm are used to extract the watermark. The experimental and simulation results show that the authorized users can get the watermark with the secret key. The watermark image could not be retrieved when the eavesdropping ratio is less than 45% with the second-order correlation algorithm, whereas it is less than 20% with the TVAL3 CS reconstructed algorithm. In addition, the proposed scheme is robust against the 'salt and pepper' noise and image cropping degradations.

Assessing treatment response in triple-negative breast cancer from quantitative image analysis in perfusion magnetic resonance imaging.

PubMed

Banerjee, Imon; Malladi, Sadhika; Lee, Daniela; Depeursinge, Adrien; Telli, Melinda; Lipson, Jafi; Golden, Daniel; Rubin, Daniel L

2018-01-01

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is sensitive but not specific to determining treatment response in early stage triple-negative breast cancer (TNBC) patients. We propose an efficient computerized technique for assessing treatment response, specifically the residual tumor (RT) status and pathological complete response (pCR), in response to neoadjuvant chemotherapy. The proposed approach is based on Riesz wavelet analysis of pharmacokinetic maps derived from noninvasive DCE-MRI scans, obtained before and after treatment. We compared the performance of Riesz features with the traditional gray level co-occurrence matrices and a comprehensive characterization of the lesion that includes a wide range of quantitative features (e.g., shape and boundary). We investigated a set of predictive models ([Formula: see text]) incorporating distinct combinations of quantitative characterizations and statistical models at different time points of the treatment and some area under the receiver operating characteristic curve (AUC) values we reported are above 0.8. The most efficient models are based on first-order statistics and Riesz wavelets, which predicted RT with an AUC value of 0.85 and pCR with an AUC value of 0.83, improving results reported in a previous study by [Formula: see text]. Our findings suggest that Riesz texture analysis of TNBC lesions can be considered a potential framework for optimizing TNBC patient care.

Characterization and treatment monitoring of inflammatory arthritis by photoacoustic imaging: a study on adjuvant-induced arthritis rat model

NASA Astrophysics Data System (ADS)

Wang, Xueding; Rajian, Justin; Shao, Xia; Chamberland, David L.; Girish, Gandikota

2014-03-01

Neovascularity also known as angiogenesis is an early feature of inflammatory arthritis disease. Therefore, identifying the development of neovascularity is one way to potentially detect and characterize arthritis. Laser-based photoacoustic imaging (PAI) is an emerging biomedical imaging modality which may aid in detection of both early and continued development of neovascularity. In this work, we investigated the feasibility of PAI to measure angiogenesis, for the purpose of evaluating and monitoring inflammatory arthritis after treatment. The imaging results on an arthritis rat model demonstrate that 1) there is noticeable enhancement in image intensity in the arthritic ankle joints when compared to the normal joints, and 2) there is noticeable decrease in image intensity in the arthritic ankle joints after treatment when compared to the untreated arthritic joints. In order to validate the findings from PAI, we performed positron emission tomography (PET) and histology on the same joints. The diameters of the ankle joints, as a clinical score of the arthritis, were also measured at each time point.

A region-based segmentation method for ultrasound images in HIFU therapy

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

Zhang, Dong, E-mail: dongz@whu.edu.cn; Liu, Yu; Yang, Yan

Purpose: Precisely and efficiently locating a tumor with less manual intervention in ultrasound-guided high-intensity focused ultrasound (HIFU) therapy is one of the keys to guaranteeing the therapeutic result and improving the efficiency of the treatment. The segmentation of ultrasound images has always been difficult due to the influences of speckle, acoustic shadows, and signal attenuation as well as the variety of tumor appearance. The quality of HIFU guidance images is even poorer than that of conventional diagnostic ultrasound images because the ultrasonic probe used for HIFU guidance usually obtains images without making contact with the patient’s body. Therefore, the segmentationmore » becomes more difficult. To solve the segmentation problem of ultrasound guidance image in the treatment planning procedure for HIFU therapy, a novel region-based segmentation method for uterine fibroids in HIFU guidance images is proposed. Methods: Tumor partitioning in HIFU guidance image without manual intervention is achieved by a region-based split-and-merge framework. A new iterative multiple region growing algorithm is proposed to first split the image into homogenous regions (superpixels). The features extracted within these homogenous regions will be more stable than those extracted within the conventional neighborhood of a pixel. The split regions are then merged by a superpixel-based adaptive spectral clustering algorithm. To ensure the superpixels that belong to the same tumor can be clustered together in the merging process, a particular construction strategy for the similarity matrix is adopted for the spectral clustering, and the similarity matrix is constructed by taking advantage of a combination of specifically selected first-order and second-order texture features computed from the gray levels and the gray level co-occurrence matrixes, respectively. The tumor region is picked out automatically from the background regions by an algorithm according to a

Validation of a deformable image registration technique for cone beam CT-based dose verification

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

Moteabbed, M., E-mail: mmoteabbed@partners.org; Sharp, G. C.; Wang, Y.

2015-01-15

Purpose: As radiation therapy evolves toward more adaptive techniques, image guidance plays an increasingly important role, not only in patient setup but also in monitoring the delivered dose and adapting the treatment to patient changes. This study aimed to validate a method for evaluation of delivered intensity modulated radiotherapy (IMRT) dose based on multimodal deformable image registration (DIR) for prostate treatments. Methods: A pelvic phantom was scanned with CT and cone-beam computed tomography (CBCT). Both images were digitally deformed using two realistic patient-based deformation fields. The original CT was then registered to the deformed CBCT resulting in a secondary deformedmore » CT. The registration quality was assessed as the ability of the DIR method to recover the artificially induced deformations. The primary and secondary deformed CT images as well as vector fields were compared to evaluate the efficacy of the registration method and it’s suitability to be used for dose calculation. PLASTIMATCH, a free and open source software was used for deformable image registration. A B-spline algorithm with optimized parameters was used to achieve the best registration quality. Geometric image evaluation was performed through voxel-based Hounsfield unit (HU) and vector field comparison. For dosimetric evaluation, IMRT treatment plans were created and optimized on the original CT image and recomputed on the two warped images to be compared. The dose volume histograms were compared for the warped structures that were identical in both warped images. This procedure was repeated for the phantom with full, half full, and empty bladder. Results: The results indicated mean HU differences of up to 120 between registered and ground-truth deformed CT images. However, when the CBCT intensities were calibrated using a region of interest (ROI)-based calibration curve, these differences were reduced by up to 60%. Similarly, the mean differences in average vector

In-vivo fluorescence lifetime imaging for monitoring the efficacy of the cancer treatment

PubMed Central

Ardeshirpour, Yasaman; Chernomordik, Victor; Hassan, Moinuddin; Zielinski, Rafal; Capala, Jacek; Gandjbakhche, Amir

2015-01-01

Purpose Advances in tumor biology created a foundation for targeted therapy aimed at inactivation of specific molecular mechanisms responsible for cell malignancy. In this paper, we used in-vivo fluorescence lifetime imaging with HER2 targeted fluorescent probes as an alternative imaging method to investigate the efficacy of targeted therapy with 17-DMAG (an HSP90 inhibitor) on tumors with high expression of HER2 receptors. Experimental Design HER2-specific Affibody, conjugated to Alexafluor 750, was injected into nude mice, bearing HER2-positive tumor xenograft. The fluorescence lifetime was measured before treatment and monitored after the probe injections at 12 hours after the last treatment dose, when the response to the 17-DMAG therapy was the most pronounced as well as a week after the last treatment when the tumors grew back almost to their pre-treatment size. Results Imaging results showed significant difference between the fluorescence lifetimes at the tumor and the contralateral site (~0.13ns) in the control group (before treatment) and 7 days after the last treatment when the tumors grew back to their pretreatment dimensions. However, at the time frame that the treatment had its maximum effect (12 hours after the last treatment) the difference between the fluorescence lifetime at the tumor and contralateral site decreased to 0.03ns. Conclusions The results showed a good correlation between fluorescence lifetime and the efficacy of the treatment. These findings show that in-vivo fluorescence lifetime imaging can be used as a promising molecular imaging tool for monitoring the treatment outcome in preclinical models and potentially in patients. PMID:24671949

Image-fusion of MR spectroscopic images for treatment planning of gliomas

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

Chang Jenghwa; Thakur, Sunitha; Perera, Gerard

2006-01-15

-fusion protocol was tested on 12 (six high-grade and six low-grade) glioma patients. The average agreement of the MRSI volume position on the screen-dumped MRSI images and the merged MRSI images was 0.29 mm with a standard deviation of 0.07 mm. Of all the voxels with Cho/Cr grade one or above, the distribution of Cho/Cr grade was found to correlate with the glioma grade from pathologic finding and is consistent with literature results indicating Cho/Cr elevation as a marker for malignancy. In conclusion, an image-fusion protocol was developed that successfully incorporates MRSI information into the IMRT treatment plan for glioma.« less

Image degradation characteristics and restoration based on regularization for diffractive imaging

NASA Astrophysics Data System (ADS)

Zhi, Xiyang; Jiang, Shikai; Zhang, Wei; Wang, Dawei; Li, Yun

2017-11-01

The diffractive membrane optical imaging system is an important development trend of ultra large aperture and lightweight space camera. However, related investigations on physics-based diffractive imaging degradation characteristics and corresponding image restoration methods are less studied. In this paper, the model of image quality degradation for the diffraction imaging system is first deduced mathematically based on diffraction theory and then the degradation characteristics are analyzed. On this basis, a novel regularization model of image restoration that contains multiple prior constraints is established. After that, the solving approach of the equation with the multi-norm coexistence and multi-regularization parameters (prior's parameters) is presented. Subsequently, the space-variant PSF image restoration method for large aperture diffractive imaging system is proposed combined with block idea of isoplanatic region. Experimentally, the proposed algorithm demonstrates its capacity to achieve multi-objective improvement including MTF enhancing, dispersion correcting, noise and artifact suppressing as well as image's detail preserving, and produce satisfactory visual quality. This can provide scientific basis for applications and possesses potential application prospects on future space applications of diffractive membrane imaging technology.

Web-based tool for visualization of electric field distribution in deep-seated body structures and planning of electroporation-based treatments

PubMed Central

2015-01-01

Background Treatments based on electroporation are a new and promising approach to treating tumors, especially non-resectable ones. The success of the treatment is, however, heavily dependent on coverage of the entire tumor volume with a sufficiently high electric field. Ensuring complete coverage in the case of deep-seated tumors is not trivial and can in best way be ensured by patient-specific treatment planning. The basis of the treatment planning process consists of two complex tasks: medical image segmentation, and numerical modeling and optimization. Methods In addition to previously developed segmentation algorithms for several tissues (human liver, hepatic vessels, bone tissue and canine brain) and the algorithms for numerical modeling and optimization of treatment parameters, we developed a web-based tool to facilitate the translation of the algorithms and their application in the clinic. The developed web-based tool automatically builds a 3D model of the target tissue from the medical images uploaded by the user and then uses this 3D model to optimize treatment parameters. The tool enables the user to validate the results of the automatic segmentation and make corrections if necessary before delivering the final treatment plan. Results Evaluation of the tool was performed by five independent experts from four different institutions. During the evaluation, we gathered data concerning user experience and measured performance times for different components of the tool. Both user reports and performance times show significant reduction in treatment-planning complexity and time-consumption from 1-2 days to a few hours. Conclusions The presented web-based tool is intended to facilitate the treatment planning process and reduce the time needed for it. It is crucial for facilitating expansion of electroporation-based treatments in the clinic and ensuring reliable treatment for the patients. The additional value of the tool is the possibility of easy upgrade and

A novel dose-based positioning method for CT image-guided proton therapy

PubMed Central

Cheung, Joey P.; Park, Peter C.; Court, Laurence E.; Ronald Zhu, X.; Kudchadker, Rajat J.; Frank, Steven J.; Dong, Lei

2013-01-01

Purpose: Proton dose distributions can potentially be altered by anatomical changes in the beam path despite perfect target alignment using traditional image guidance methods. In this simulation study, the authors explored the use of dosimetric factors instead of only anatomy to set up patients for proton therapy using in-room volumetric computed tomographic (CT) images. Methods: To simulate patient anatomy in a free-breathing treatment condition, weekly time-averaged four-dimensional CT data near the end of treatment for 15 lung cancer patients were used in this study for a dose-based isocenter shift method to correct dosimetric deviations without replanning. The isocenter shift was obtained using the traditional anatomy-based image guidance method as the starting position. Subsequent isocenter shifts were established based on dosimetric criteria using a fast dose approximation method. For each isocenter shift, doses were calculated every 2 mm up to ±8 mm in each direction. The optimal dose alignment was obtained by imposing a target coverage constraint that at least 99% of the target would receive at least 95% of the prescribed dose and by minimizing the mean dose to the ipsilateral lung. Results: The authors found that 7 of 15 plans did not meet the target coverage constraint when using only the anatomy-based alignment. After the authors applied dose-based alignment, all met the target coverage constraint. For all but one case in which the target dose was met using both anatomy-based and dose-based alignment, the latter method was able to improve normal tissue sparing. Conclusions: The authors demonstrated that a dose-based adjustment to the isocenter can improve target coverage and/or reduce dose to nearby normal tissue. PMID:23635262

Use of fluorine-18-BPA PET images and image registration to enhance radiation treatment planning for boron neutron capture therapy

NASA Astrophysics Data System (ADS)

Khan, Mohammad Khurram

The Monte-Carlo based simulation environment for radiation therapy (SERA) software is used to simulate the dose administered to a patient undergoing boron neutron capture therapy (BNCT). Point sampling of tumor tissue results in an estimate of a uniform boron concentration scaling factor of 3.5. Under conventional treatment protocols, this factor is used to scale the boron component of the dose linearly and homogenously within the tumor and target volumes. The average dose to the tumor cells by such a method could be improved by better methods of quantifying the in-vivo 10B biodistribution. A better method includes radiolabeling para-Boronophenylalanine (p-BPA) with 18F and imaging the pharmaceutical using positron emission tomography (PET). This biodistribution of 18F-BPA can then be used to better predict the average dose delivered to the tumor regions. This work uses registered 18F-BPA PET images to incorporate the in-vivo boron biodistribution within current treatment planning. The registered 18F-BPA PET images are then coupled in a new computer software, PET2MRI.m, to linearly scale the boron component of the dose. A qualititative and quantitative assessment of the dose contours is presented using the two approaches. Tumor volume, tumor axial extent, and target locations are compared between using MRI or PET images to define the tumor volume. In addition, peak-to-normal brain value at tumor axial center is determined for pre and post surgery patients using 18F-BPA PET images. The differences noted between the registered GBM tumor volumes (range: 34.04--136.36%), tumor axial extent (range: 20--150%), and the beam target location (1.27--4.29 cm) are significantly different. The peak-to-normal brain values are also determined at the tumor axial center using the 18F-BPA PET images. The peak-to-normal brain values using the last frame of the pre-surgery study for the GBM patients ranged from 2.05--3.4. For post surgery time weighted PET data, the peak

Treatment of Body Image Dissatisfaction among Women with Bulimia Nervosa.

ERIC Educational Resources Information Center

Brouwers, Mariette

1990-01-01

Sees body image dissatisfaction as contributing to development and maintenance of bulimia nervosa and bulimic's desire for thinness breeding low self-esteem, feelings of inadequacy, and resistance to recovery. Offers treatment suggestions for body image dissatisfaction as it relates to bulimia. Advises counselors to be satisfied with their own…

Effectiveness of image features and similarity measures in cluster-based approaches for content-based image retrieval

NASA Astrophysics Data System (ADS)

Du, Hongbo; Al-Jubouri, Hanan; Sellahewa, Harin

2014-05-01

Content-based image retrieval is an automatic process of retrieving images according to image visual contents instead of textual annotations. It has many areas of application from automatic image annotation and archive, image classification and categorization to homeland security and law enforcement. The key issues affecting the performance of such retrieval systems include sensible image features that can effectively capture the right amount of visual contents and suitable similarity measures to find similar and relevant images ranked in a meaningful order. Many different approaches, methods and techniques have been developed as a result of very intensive research in the past two decades. Among many existing approaches, is a cluster-based approach where clustering methods are used to group local feature descriptors into homogeneous regions, and search is conducted by comparing the regions of the query image against those of the stored images. This paper serves as a review of works in this area. The paper will first summarize the existing work reported in the literature and then present the authors' own investigations in this field. The paper intends to highlight not only achievements made by recent research but also challenges and difficulties still remaining in this area.

Content-Based Medical Image Retrieval

NASA Astrophysics Data System (ADS)

Müller, Henning; Deserno, Thomas M.

This chapter details the necessity for alternative access concepts to the currently mainly text-based methods in medical information retrieval. This need is partly due to the large amount of visual data produced, the increasing variety of medical imaging data and changing user patterns. The stored visual data contain large amounts of unused information that, if well exploited, can help diagnosis, teaching and research. The chapter briefly reviews the history of image retrieval and its general methods before technologies that have been developed in the medical domain are focussed. We also discuss evaluation of medical content-based image retrieval (CBIR) systems and conclude with pointing out their strengths, gaps, and further developments. As examples, the MedGIFT project and the Image Retrieval in Medical Applications (IRMA) framework are presented.

Evaluation of chemotherapy response in ovarian cancer treatment using quantitative CT image biomarkers: a preliminary study

NASA Astrophysics Data System (ADS)

Qiu, Yuchen; Tan, Maxine; McMeekin, Scott; Thai, Theresa; Moore, Kathleen; Ding, Kai; Liu, Hong; Zheng, Bin

2015-03-01

The purpose of this study is to identify and apply quantitative image biomarkers for early prediction of the tumor response to the chemotherapy among the ovarian cancer patients participated in the clinical trials of testing new drugs. In the experiment, we retrospectively selected 30 cases from the patients who participated in Phase I clinical trials of new drug or drug agents for ovarian cancer treatment. Each case is composed of two sets of CT images acquired pre- and post-treatment (4-6 weeks after starting treatment). A computer-aided detection (CAD) scheme was developed to extract and analyze the quantitative image features of the metastatic tumors previously tracked by the radiologists using the standard Response Evaluation Criteria in Solid Tumors (RECIST) guideline. The CAD scheme first segmented 3-D tumor volumes from the background using a hybrid tumor segmentation scheme. Then, for each segmented tumor, CAD computed three quantitative image features including the change of tumor volume, tumor CT number (density) and density variance. The feature changes were calculated between the matched tumors tracked on the CT images acquired pre- and post-treatments. Finally, CAD predicted patient's 6-month progression-free survival (PFS) using a decision-tree based classifier. The performance of the CAD scheme was compared with the RECIST category. The result shows that the CAD scheme achieved a prediction accuracy of 76.7% (23/30 cases) with a Kappa coefficient of 0.493, which is significantly higher than the performance of RECIST prediction with a prediction accuracy and Kappa coefficient of 60% (17/30) and 0.062, respectively. This study demonstrated the feasibility of analyzing quantitative image features to improve the early predicting accuracy of the tumor response to the new testing drugs or therapeutic methods for the ovarian cancer patients.

Online updating of context-aware landmark detectors for prostate localization in daily treatment CT images

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

Dai, Xiubin; Gao, Yaozong; Shen, Dinggang, E-mail: dgshen@med.unc.edu

2015-05-15

Purpose: In image guided radiation therapy, it is crucial to fast and accurately localize the prostate in the daily treatment images. To this end, the authors propose an online update scheme for landmark-guided prostate segmentation, which can fully exploit valuable patient-specific information contained in the previous treatment images and can achieve improved performance in landmark detection and prostate segmentation. Methods: To localize the prostate in the daily treatment images, the authors first automatically detect six anatomical landmarks on the prostate boundary by adopting a context-aware landmark detection method. Specifically, in this method, a two-layer regression forest is trained as amore » detector for each target landmark. Once all the newly detected landmarks from new treatment images are reviewed or adjusted (if necessary) by clinicians, they are further included into the training pool as new patient-specific information to update all the two-layer regression forests for the next treatment day. As more and more treatment images of the current patient are acquired, the two-layer regression forests can be continually updated by incorporating the patient-specific information into the training procedure. After all target landmarks are detected, a multiatlas random sample consensus (multiatlas RANSAC) method is used to segment the entire prostate by fusing multiple previously segmented prostates of the current patient after they are aligned to the current treatment image. Subsequently, the segmented prostate of the current treatment image is again reviewed (or even adjusted if needed) by clinicians before including it as a new shape example into the prostate shape dataset for helping localize the entire prostate in the next treatment image. Results: The experimental results on 330 images of 24 patients show the effectiveness of the authors’ proposed online update scheme in improving the accuracies of both landmark detection and prostate

MR Imaging in Monitoring and Predicting Treatment Response in Multiple Sclerosis.

PubMed

Río, Jordi; Auger, Cristina; Rovira, Àlex

2017-05-01

MR imaging is the most sensitive tool for identifying lesions in patients with multiple sclerosis (MS). MR imaging has also acquired an essential role in the detection of complications arising from these treatments and in the assessment and prediction of efficacy. In the future, other radiological measures that have shown prognostic value may be incorporated within the models for predicting treatment response. This article examines the role of MR imaging as a prognostic tool in patients with MS and the recommendations that have been proposed in recent years to monitor patients who are treated with disease-modifying drugs. Copyright © 2017 Elsevier Inc. All rights reserved.

Office-based dynamic imaging of vocal cords in awake patients with swept-source optical coherence tomography

NASA Astrophysics Data System (ADS)

Yu, Lingfeng; Liu, Gangjun; Rubinstein, Marc; Saidi, Arya; Wong, Brian J. F.; Chen, Zhongping

2009-11-01

Optical coherence tomography (OCT) is an evolving noninvasive imaging modality that has been used to image the human larynx during surgical endoscopy. The design of a long gradient index (GRIN) lens-based probe capable of capturing images of the human larynx by use of swept-source OCT during a typical office-based laryngoscopy examination is presented. In vivo OCT imaging of the human larynx is demonstrated with a rate of 40 frames per second. Dynamic vibration of the vocal folds is recorded to provide not only high-resolution cross-sectional tissue structures but also vibration parameters, such as the vibration frequency and magnitude of the vocal cords, which provides important information for clinical diagnosis and treatment, as well as fundamental research of the voice itself. Office-based OCT is a promising imaging modality to study the larynx for physicians in otolaryngology.

Office-based dynamic imaging of vocal cords in awake patients with swept-source optical coherence tomography.

PubMed

Yu, Lingfeng; Liu, Gangjun; Rubinstein, Marc; Saidi, Arya; Wong, Brian J F; Chen, Zhongping

2009-01-01

Optical coherence tomography (OCT) is an evolving noninvasive imaging modality that has been used to image the human larynx during surgical endoscopy. The design of a long gradient index (GRIN) lens-based probe capable of capturing images of the human larynx by use of swept-source OCT during a typical office-based laryngoscopy examination is presented. In vivo OCT imaging of the human larynx is demonstrated with a rate of 40 frames per second. Dynamic vibration of the vocal folds is recorded to provide not only high-resolution cross-sectional tissue structures but also vibration parameters, such as the vibration frequency and magnitude of the vocal cords, which provides important information for clinical diagnosis and treatment, as well as fundamental research of the voice itself. Office-based OCT is a promising imaging modality to study the larynx for physicians in otolaryngology.

Office-based dynamic imaging of vocal cords in awake patients with swept-source optical coherence tomography

PubMed Central

Yu, Lingfeng; Liu, Gangjun; Rubinstein, Marc; Saidi, Arya; Wong, Brian J.F.; Chen, Zhongping

2009-01-01

Optical coherence tomography (OCT) is an evolving noninvasive imaging modality that has been used to image the human larynx during surgical endoscopy. The design of a long gradient index (GRIN) lens–based probe capable of capturing images of the human larynx by use of swept-source OCT during a typical office-based laryngoscopy examination is presented. In vivo OCT imaging of the human larynx is demonstrated with a rate of 40 frames per second. Dynamic vibration of the vocal folds is recorded to provide not only high-resolution cross-sectional tissue structures but also vibration parameters, such as the vibration frequency and magnitude of the vocal cords, which provides important information for clinical diagnosis and treatment, as well as fundamental research of the voice itself. Office-based OCT is a promising imaging modality to study the larynx for physicians in otolaryngology. PMID:20059258

Whole-body hybrid imaging concept for the integration of PET/MR into radiation therapy treatment planning.

PubMed

Paulus, Daniel H; Oehmigen, Mark; Grüneisen, Johannes; Umutlu, Lale; Quick, Harald H

2016-05-07

Modern radiation therapy (RT) treatment planning is based on multimodality imaging. With the recent availability of whole-body PET/MR hybrid imaging new opportunities arise to improve target volume delineation in RT treatment planning. This, however, requires dedicated RT equipment for reproducible patient positioning on the PET/MR system, which has to be compatible with MR and PET imaging. A prototype flat RT table overlay, radiofrequency (RF) coil holders for head imaging, and RF body bridges for body imaging were developed and tested towards PET/MR system integration. Attenuation correction (AC) of all individual RT components was performed by generating 3D CT-based template models. A custom-built program for μ-map generation assembles all AC templates depending on the presence and position of each RT component. All RT devices were evaluated in phantom experiments with regards to MR and PET imaging compatibility, attenuation correction, PET quantification, and position accuracy. The entire RT setup was then evaluated in a first PET/MR patient study on five patients at different body regions. All tested devices are PET/MR compatible and do not produce visible artifacts or disturb image quality. The RT components showed a repositioning accuracy of better than 2 mm. Photon attenuation of  -11.8% in the top part of the phantom was observable, which was reduced to  -1.7% with AC using the μ-map generator. Active lesions of 3 subjects were evaluated in terms of SUVmean and an underestimation of  -10.0% and  -2.4% was calculated without and with AC of the RF body bridges, respectively. The new dedicated RT equipment for hybrid PET/MR imaging enables acquisitions in all body regions. It is compatible with PET/MR imaging and all hardware components can be corrected in hardware AC by using the suggested μ-map generator. These developments provide the technical and methodological basis for integration of PET/MR hybrid imaging into RT planning.

SU-F-303-11: Implementation and Applications of Rapid, SIFT-Based Cine MR Image Binning and Region Tracking

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

Mazur, T; Wang, Y; Fischer-Valuck, B

2015-06-15

Purpose: To develop a novel and rapid, SIFT-based algorithm for assessing feature motion on cine MR images acquired during MRI-guided radiotherapy treatments. In particular, we apply SIFT descriptors toward both partitioning cine images into respiratory states and tracking regions across frames. Methods: Among a training set of images acquired during a fraction, we densely assign SIFT descriptors to pixels within the images. We cluster these descriptors across all frames in order to produce a dictionary of trackable features. Associating the best-matching descriptors at every frame among the training images to these features, we construct motion traces for the features. Wemore » use these traces to define respiratory bins for sorting images in order to facilitate robust pixel-by-pixel tracking. Instead of applying conventional methods for identifying pixel correspondences across frames we utilize a recently-developed algorithm that derives correspondences via a matching objective for SIFT descriptors. Results: We apply these methods to a collection of lung, abdominal, and breast patients. We evaluate the procedure for respiratory binning using target sites exhibiting high-amplitude motion among 20 lung and abdominal patients. In particular, we investigate whether these methods yield minimal variation between images within a bin by perturbing the resulting image distributions among bins. Moreover, we compare the motion between averaged images across respiratory states to 4DCT data for these patients. We evaluate the algorithm for obtaining pixel correspondences between frames by tracking contours among a set of breast patients. As an initial case, we track easily-identifiable edges of lumpectomy cavities that show minimal motion over treatment. Conclusions: These SIFT-based methods reliably extract motion information from cine MR images acquired during patient treatments. While we performed our analysis retrospectively, the algorithm lends itself to prospective

In vivo fluorescence lifetime imaging for monitoring the efficacy of the cancer treatment.

PubMed

Ardeshirpour, Yasaman; Chernomordik, Victor; Hassan, Moinuddin; Zielinski, Rafal; Capala, Jacek; Gandjbakhche, Amir

2014-07-01

Advances in tumor biology created a foundation for targeted therapy aimed at inactivation of specific molecular mechanisms responsible for cell malignancy. In this paper, we used in vivo fluorescence lifetime imaging with HER2-targeted fluorescent probes as an alternative imaging method to investigate the efficacy of targeted therapy with 17-DMAG (an HSP90 inhibitor) on tumors with high expression of HER2 receptors. HER2-specific Affibody, conjugated to Alexafluor 750, was injected into nude mice bearing HER2-positive tumor xenograft. The fluorescence lifetime was measured before treatment and monitored after the probe injections at 12 hours after the last treatment dose, when the response to the 17-DMAG therapy was the most pronounced as well as a week after the last treatment when the tumors grew back almost to their pretreatment size. Imaging results showed significant difference between the fluorescence lifetimes at the tumor and the contralateral site (∼0.13 ns) in the control group (before treatment) and 7 days after the last treatment when the tumors grew back to their pretreatment dimensions. However, at the time frame that the treatment had its maximum effect (12 hours after the last treatment), the difference between the fluorescence lifetime at the tumor and contralateral site decreased to 0.03 ns. The results showed a good correlation between fluorescence lifetime and the efficacy of the treatment. These findings show that in vivo fluorescence lifetime imaging can be used as a promising molecular imaging tool for monitoring the treatment outcome in preclinical models and potentially in patients. ©2014 American Association for Cancer Research.

A Novel, Aqueous Surface Treatment To Thermally Stabilize High Resolution Positive Photoresist Images*

NASA Astrophysics Data System (ADS)

Grunwald, John J.; Spencer, Allen C.

1986-07-01

The paper describes a new approach to thermally stabilize the already imaged profile of high resolution positive photoresists such as ULTRAMAC" PR-914. ***XD-4000, an aqueous emulsion of a blend of fluorine-bearing compounds is spun on top of the developed, positive photoresist-imaged wafer, and baked. This allows the photoresist to withstand temperatures up to at least 175 deg. C. while essentially maintaining vertical edge profiles. Also, adverse effects of "outgassing" in harsh environments, ie., plasma and ion implant are greatly minimized by allowing the high resolution imaged photoresist to be post-baked at "elevated" temperatures. Another type of product that accomplishes the same effect is ***XD-4005, an aqueous emulsion of a high temperature-resistant polymer. While the exact mechanism is yet to be identified, it is postulated that absorption of the "polymeric" species into the "skin" of the imaged resist forms a temperature resistant "envelope", thereby allowing high resolution photoresists to also serve in a "high temperature" mode, without reticulation, or other adverse effects due to thermal degradation. SEM's are presented showing imaged ULTRAMAC" PR-914 and ULTRAMAC" **EPA-914 geometries coated with XD-4000 or XD-4005 and followed by plasma etched oxide,polysilicon and aluminum. Selectivity ratios are compared with and without the novel treatment and are shown to be significantly better with the treatment. The surface-treated photoresist for thermal resistance remains easily strippable in solvent-based or plasma media, unlike photoresists that have undergone "PRIST" or other gaseous thermal stabilization methods.

Radiotherapy treatment planning: benefits of CT-MR image registration and fusion in tumor volume delineation.

PubMed

Djan, Igor; Petrović, Borislava; Erak, Marko; Nikolić, Ivan; Lucić, Silvija

2013-08-01

Development of imaging techniques, computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET), made great impact on radiotherapy treatment planning by improving the localization of target volumes. Improved localization allows better local control of tumor volumes, but also minimizes geographical misses. Mutual information is obtained by registration and fusion of images achieved manually or automatically. The aim of this study was to validate the CT-MRI image fusion method and compare delineation obtained by CT versus CT-MRI image fusion. The image fusion software (XIO CMS 4.50.0) was applied to delineate 16 patients. The patients were scanned on CT and MRI in the treatment position within an immobilization device before the initial treatment. The gross tumor volume (GTV) and clinical target volume (CTV) were delineated on CT alone and on CT+MRI images consecutively and image fusion was obtained. Image fusion showed that CTV delineated on a CT image study set is mainly inadequate for treatment planning, in comparison with CTV delineated on CT-MRI fused image study set. Fusion of different modalities enables the most accurate target volume delineation. This study shows that registration and image fusion allows precise target localization in terms of GTV and CTV and local disease control.

Automatic tissue image segmentation based on image processing and deep learning

NASA Astrophysics Data System (ADS)

Kong, Zhenglun; Luo, Junyi; Xu, Shengpu; Li, Ting

2018-02-01

Image segmentation plays an important role in multimodality imaging, especially in fusion structural images offered by CT, MRI with functional images collected by optical technologies or other novel imaging technologies. Plus, image segmentation also provides detailed structure description for quantitative visualization of treating light distribution in the human body when incorporated with 3D light transport simulation method. Here we used image enhancement, operators, and morphometry methods to extract the accurate contours of different tissues such as skull, cerebrospinal fluid (CSF), grey matter (GM) and white matter (WM) on 5 fMRI head image datasets. Then we utilized convolutional neural network to realize automatic segmentation of images in a deep learning way. We also introduced parallel computing. Such approaches greatly reduced the processing time compared to manual and semi-automatic segmentation and is of great importance in improving speed and accuracy as more and more samples being learned. Our results can be used as a criteria when diagnosing diseases such as cerebral atrophy, which is caused by pathological changes in gray matter or white matter. We demonstrated the great potential of such image processing and deep leaning combined automatic tissue image segmentation in personalized medicine, especially in monitoring, and treatments.

Developing Students' Ideas about Lens Imaging: Teaching Experiments with an Image-Based Approach

ERIC Educational Resources Information Center

Grusche, Sascha

2017-01-01

Lens imaging is a classic topic in physics education. To guide students from their holistic viewpoint to the scientists' analytic viewpoint, an image-based approach to lens imaging has recently been proposed. To study the effect of the image-based approach on undergraduate students' ideas, teaching experiments are performed and evaluated using…

Voxel-based statistical analysis of uncertainties associated with deformable image registration

NASA Astrophysics Data System (ADS)

Li, Shunshan; Glide-Hurst, Carri; Lu, Mei; Kim, Jinkoo; Wen, Ning; Adams, Jeffrey N.; Gordon, James; Chetty, Indrin J.; Zhong, Hualiang

2013-09-01

Deformable image registration (DIR) algorithms have inherent uncertainties in their displacement vector fields (DVFs).The purpose of this study is to develop an optimal metric to estimate DIR uncertainties. Six computational phantoms have been developed from the CT images of lung cancer patients using a finite element method (FEM). The FEM generated DVFs were used as a standard for registrations performed on each of these phantoms. A mechanics-based metric, unbalanced energy (UE), was developed to evaluate these registration DVFs. The potential correlation between UE and DIR errors was explored using multivariate analysis, and the results were validated by landmark approach and compared with two other error metrics: DVF inverse consistency (IC) and image intensity difference (ID). Landmark-based validation was performed using the POPI-model. The results show that the Pearson correlation coefficient between UE and DIR error is rUE-error = 0.50. This is higher than rIC-error = 0.29 for IC and DIR error and rID-error = 0.37 for ID and DIR error. The Pearson correlation coefficient between UE and the product of the DIR displacements and errors is rUE-error × DVF = 0.62 for the six patients and rUE-error × DVF = 0.73 for the POPI-model data. It has been demonstrated that UE has a strong correlation with DIR errors, and the UE metric outperforms the IC and ID metrics in estimating DIR uncertainties. The quantified UE metric can be a useful tool for adaptive treatment strategies, including probability-based adaptive treatment planning.

Pc-Based Floating Point Imaging Workstation

NASA Astrophysics Data System (ADS)

Guzak, Chris J.; Pier, Richard M.; Chinn, Patty; Kim, Yongmin

1989-07-01

The medical, military, scientific and industrial communities have come to rely on imaging and computer graphics for solutions to many types of problems. Systems based on imaging technology are used to acquire and process images, and analyze and extract data from images that would otherwise be of little use. Images can be transformed and enhanced to reveal detail and meaning that would go undetected without imaging techniques. The success of imaging has increased the demand for faster and less expensive imaging systems and as these systems become available, more and more applications are discovered and more demands are made. From the designer's perspective the challenge to meet these demands forces him to attack the problem of imaging from a different perspective. The computing demands of imaging algorithms must be balanced against the desire for affordability and flexibility. Systems must be flexible and easy to use, ready for current applications but at the same time anticipating new, unthought of uses. Here at the University of Washington Image Processing Systems Lab (IPSL) we are focusing our attention on imaging and graphics systems that implement imaging algorithms for use in an interactive environment. We have developed a PC-based imaging workstation with the goal to provide powerful and flexible, floating point processing capabilities, along with graphics functions in an affordable package suitable for diverse environments and many applications.

Hyperspectral Imaging of Functional Patterns for Disease Assessment and Treatment Monitoring

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

Demos, S; Hattery, D; Hassan, M

2003-12-05

We have designed and built a six-band multi-spectral NIR imaging system used in clinical testing on cancer patients. From our layered tissue model, we create blood volume and blood oxygenation images for patient treatment monitoring.

SU-G-JeP3-06: Lower KV Image Dose Are Expected From a Limited-Angle Intra-Fractional Verification (LIVE) System for SBRT Treatments

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

Ding, G; Yin, F; Ren, L

Purpose: In order to track the tumor movement for patient positioning verification during arc treatment delivery or in between 3D/IMRT beams for stereotactic body radiation therapy (SBRT), the limited-angle kV projections acquisition simultaneously during arc treatment delivery or in-between static treatment beams as the gantry moves to the next beam angle was proposed. The purpose of this study is to estimate additional imaging dose resulting from multiple tomosynthesis acquisitions in-between static treatment beams and to compare with that of a conventional kV-CBCT acquisition. Methods: kV imaging system integrated into Varian TrueBeam accelerators was modeled using EGSnrc Monte Carlo user code,more » BEAMnrc and DOSXYZnrc code was used in dose calculations. The simulated realistic kV beams from the Varian TrueBeam OBI 1.5 system were used to calculate dose to patient based on CT images. Organ doses were analyzed using DVHs. The imaging dose to patient resulting from realistic multiple tomosynthesis acquisitions with each 25–30 degree kV source rotation between 6 treatment beam gantry angles was studied. Results: For a typical lung SBRT treatment delivery much lower (20–50%) kV imaging doses from the sum of realistic six tomosynthesis acquisitions with each 25–30 degree x-ray source rotation between six treatment beam gantry angles were observed compared to that from a single CBCT image acquisition. Conclusion: This work indicates that the kV imaging in this proposed Limited-angle Intra-fractional Verification (LIVE) System for SBRT Treatments has a negligible imaging dose increase. It is worth to note that the MV imaging dose caused by MV projection acquisition in-between static beams in LIVE can be minimized by restricting the imaging to the target region and reducing the number of projections acquired. For arc treatments, MV imaging acquisition in LIVE does not add additional imaging dose as the MV images are acquired from treatment beams directly

Uterine leiomyomas: histopathologic features, MR imaging findings, differential diagnosis, and treatment.

PubMed

Murase, E; Siegelman, E S; Outwater, E K; Perez-Jaffe, L A; Tureck, R W

1999-01-01

Leiomyomas are the most common uterine neoplasm and are composed of smooth muscle with varying amounts of fibrous connective tissue. As leiomyomas enlarge, they may outgrow their blood supply, resulting in various types of degeneration: hyaline or myxoid degeneration, calcification, cystic degeneration, and red degeneration. Leiomyomas are classified as submucosal, intramural, or subserosal; the latter may become pedunculated and simulate ovarian neoplasms. Although most leiomyomas are asymptomatic, patients may present with abnormal uterine bleeding, pressure on adjacent organs, pain, infertility, or a palpable abdominalpelvic mass. Magnetic resonance (MR) imaging is the most accurate imaging technique for detection and localization of leiomyomas. On T2-weighted images, nondegenerated leiomyomas appear as well-circumscribed masses of decreased signal intensity; however, cellular leiomyomas can have relatively higher signal intensity on T2-weighted images and demonstrate enhancement on contrast material-enhanced images. Degenerated leiomyomas have variable appearances on T2-weighted images and contrast-enhanced images. The differential diagnosis of leiomyomas includes adenomyosis, solid adnexal mass, focal myometrial contraction, and uterine leiomyosarcoma. For patients with symptoms, medical or surgical treatment may be indicated. MR imaging also has a role in treatment of leiomyomas by assisting in surgical planning and monitoring the response to medical therapy.

WE-EF-210-08: BEST IN PHYSICS (IMAGING): 3D Prostate Segmentation in Ultrasound Images Using Patch-Based Anatomical Feature

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

Yang, X; Rossi, P; Jani, A

Purpose: Transrectal ultrasound (TRUS) is the standard imaging modality for the image-guided prostate-cancer interventions (e.g., biopsy and brachytherapy) due to its versatility and real-time capability. Accurate segmentation of the prostate plays a key role in biopsy needle placement, treatment planning, and motion monitoring. As ultrasound images have a relatively low signal-to-noise ratio (SNR), automatic segmentation of the prostate is difficult. However, manual segmentation during biopsy or radiation therapy can be time consuming. We are developing an automated method to address this technical challenge. Methods: The proposed segmentation method consists of two major stages: the training stage and the segmentation stage.more » During the training stage, patch-based anatomical features are extracted from the registered training images with patient-specific information, because these training images have been mapped to the new patient’ images, and the more informative anatomical features are selected to train the kernel support vector machine (KSVM). During the segmentation stage, the selected anatomical features are extracted from newly acquired image as the input of the well-trained KSVM and the output of this trained KSVM is the segmented prostate of this patient. Results: This segmentation technique was validated with a clinical study of 10 patients. The accuracy of our approach was assessed using the manual segmentation. The mean volume Dice Overlap Coefficient was 89.7±2.3%, and the average surface distance was 1.52 ± 0.57 mm between our and manual segmentation, which indicate that the automatic segmentation method works well and could be used for 3D ultrasound-guided prostate intervention. Conclusion: We have developed a new prostate segmentation approach based on the optimal feature learning framework, demonstrated its clinical feasibility, and validated its accuracy with manual segmentation (gold standard). This segmentation technique could be a

a Region-Based Multi-Scale Approach for Object-Based Image Analysis

NASA Astrophysics Data System (ADS)

Kavzoglu, T.; Yildiz Erdemir, M.; Tonbul, H.

2016-06-01

Within the last two decades, object-based image analysis (OBIA) considering objects (i.e. groups of pixels) instead of pixels has gained popularity and attracted increasing interest. The most important stage of the OBIA is image segmentation that groups spectrally similar adjacent pixels considering not only the spectral features but also spatial and textural features. Although there are several parameters (scale, shape, compactness and band weights) to be set by the analyst, scale parameter stands out the most important parameter in segmentation process. Estimating optimal scale parameter is crucially important to increase the classification accuracy that depends on image resolution, image object size and characteristics of the study area. In this study, two scale-selection strategies were implemented in the image segmentation process using pan-sharped Qickbird-2 image. The first strategy estimates optimal scale parameters for the eight sub-regions. For this purpose, the local variance/rate of change (LV-RoC) graphs produced by the ESP-2 tool were analysed to determine fine, moderate and coarse scales for each region. In the second strategy, the image was segmented using the three candidate scale values (fine, moderate, coarse) determined from the LV-RoC graph calculated for whole image. The nearest neighbour classifier was applied in all segmentation experiments and equal number of pixels was randomly selected to calculate accuracy metrics (overall accuracy and kappa coefficient). Comparison of region-based and image-based segmentation was carried out on the classified images and found that region-based multi-scale OBIA produced significantly more accurate results than image-based single-scale OBIA. The difference in classification accuracy reached to 10% in terms of overall accuracy.

MO-A-BRD-06: In Vivo Cherenkov Video Imaging to Verify Whole Breast Irradiation Treatment

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

Zhang, R; Glaser, A; Jarvis, L

Purpose: To show in vivo video imaging of Cherenkov emission (Cherenkoscopy) can be acquired in the clinical treatment room without affecting the normal process of external beam radiation therapy (EBRT). Applications of Cherenkoscopy, such as patient positioning, movement tracking, treatment monitoring and superficial dose estimation, were examined. Methods: In a phase 1 clinical trial, including 12 patients undergoing post-lumpectomy whole breast irradiation, Cherenkov emission was imaged with a time-gated ICCD camera synchronized to the radiation pulses, during 10 fractions of the treatment. Images from different treatment days were compared by calculating the 2-D correlations corresponding to the averaged image. Anmore » edge detection algorithm was utilized to highlight biological features, such as the blood vessels. Superficial dose deposited at the sampling depth were derived from the Eclipse treatment planning system (TPS) and compared with the Cherenkov images. Skin reactions were graded weekly according to the Common Toxicity Criteria and digital photographs were obtained for comparison. Results: Real time (fps = 4.8) imaging of Cherenkov emission was feasible and feasibility tests indicated that it could be improved to video rate (fps = 30) with system improvements. Dynamic field changes due to fast MLC motion were imaged in real time. The average 2-D correlation was about 0.99, suggesting the stability of this imaging technique and repeatability of patient positioning was outstanding. Edge enhanced images of blood vessels were observed, and could serve as unique biological markers for patient positioning and movement tracking (breathing). Small discrepancies exists between the Cherenkov images and the superficial dose predicted from the TPS but the former agreed better with actual skin reactions than did the latter. Conclusion: Real time Cherenkoscopy imaging during EBRT is a novel imaging tool that could be utilized for patient positioning, movement

Measurable realistic image-based 3D mapping

NASA Astrophysics Data System (ADS)

Liu, W.; Wang, J.; Wang, J. J.; Ding, W.; Almagbile, A.

2011-12-01

Maps with 3D visual models are becoming a remarkable feature of 3D map services. High-resolution image data is obtained for the construction of 3D visualized models.The3D map not only provides the capabilities of 3D measurements and knowledge mining, but also provides the virtual experienceof places of interest, such as demonstrated in the Google Earth. Applications of 3D maps are expanding into the areas of architecture, property management, and urban environment monitoring. However, the reconstruction of high quality 3D models is time consuming, and requires robust hardware and powerful software to handle the enormous amount of data. This is especially for automatic implementation of 3D models and the representation of complicated surfacesthat still need improvements with in the visualisation techniques. The shortcoming of 3D model-based maps is the limitation of detailed coverage since a user can only view and measure objects that are already modelled in the virtual environment. This paper proposes and demonstrates a 3D map concept that is realistic and image-based, that enables geometric measurements and geo-location services. Additionally, image-based 3D maps provide more detailed information of the real world than 3D model-based maps. The image-based 3D maps use geo-referenced stereo images or panoramic images. The geometric relationships between objects in the images can be resolved from the geometric model of stereo images. The panoramic function makes 3D maps more interactive with users but also creates an interesting immersive circumstance. Actually, unmeasurable image-based 3D maps already exist, such as Google street view, but only provide virtual experiences in terms of photos. The topographic and terrain attributes, such as shapes and heights though are omitted. This paper also discusses the potential for using a low cost land Mobile Mapping System (MMS) to implement realistic image 3D mapping, and evaluates the positioning accuracy that a measureable

A fiducial detection algorithm for real-time image guided IMRT based on simultaneous MV and kV imaging

PubMed Central

Mao, Weihua; Riaz, Nadeem; Lee, Louis; Wiersma, Rodney; Xing, Lei

2008-01-01

The advantage of highly conformal dose techniques such as 3DCRT and IMRT is limited by intrafraction organ motion. A new approach to gain near real-time 3D positions of internally implanted fiducial markers is to analyze simultaneous onboard kV beam and treatment MV beam images (from fluoroscopic or electronic portal image devices). Before we can use this real-time image guidance for clinical 3DCRT and IMRT treatments, four outstanding issues need to be addressed. (1) How will fiducial motion blur the image and hinder tracking fiducials? kV and MV images are acquired while the tumor is moving at various speeds. We find that a fiducial can be successfully detected at a maximum linear speed of 1.6 cm∕s. (2) How does MV beam scattering affect kV imaging? We investigate this by varying MV field size and kV source to imager distance, and find that common treatment MV beams do not hinder fiducial detection in simultaneous kV images. (3) How can one detect fiducials on images from 3DCRT and IMRT treatment beams when the MV fields are modified by a multileaf collimator (MLC)? The presented analysis is capable of segmenting a MV field from the blocking MLC and detecting visible fiducials. This enables the calculation of nearly real-time 3D positions of markers during a real treatment. (4) Is the analysis fast enough to track fiducials in nearly real time? Multiple methods are adopted to predict marker positions and reduce search regions. The average detection time per frame for three markers in a 1024×768 image was reduced to 0.1 s or less. Solving these four issues paves the way to tracking moving fiducial markers throughout a 3DCRT or IMRT treatment. Altogether, these four studies demonstrate that our algorithm can track fiducials in real time, on degraded kV images (MV scatter), in rapidly moving tumors (fiducial blurring), and even provide useful information in the case when some fiducials are blocked from view by the MLC. This technique can provide a gating signal

B-spline based image tracking by detection

NASA Astrophysics Data System (ADS)

Balaji, Bhashyam; Sithiravel, Rajiv; Damini, Anthony; Kirubarajan, Thiagalingam; Rajan, Sreeraman

2016-05-01

Visual image tracking involves the estimation of the motion of any desired targets in a surveillance region using a sequence of images. A standard method of isolating moving targets in image tracking uses background subtraction. The standard background subtraction method is often impacted by irrelevant information in the images, which can lead to poor performance in image-based target tracking. In this paper, a B-Spline based image tracking is implemented. The novel method models the background and foreground using the B-Spline method followed by a tracking-by-detection algorithm. The effectiveness of the proposed algorithm is demonstrated.

Imaging approaches for the study of cell based cardiac therapies

PubMed Central

Lau, Joe F.; Anderson, Stasia A.; Adler, Eric; Frank, Joseph A.

2009-01-01

Despite promising preclinical data, the treatment of cardiovascular diseases using embryonic, bone-marrow-derived, and skeletal myoblast stem cells has not yet come to fruition within mainstream clinical practice. Major obstacles in cardiac stem cell investigations include the ability to monitor cell engraftment and survival following implantation within the myocardium. Several cellular imaging modalities, including reporter gene and MRI-based tracking approaches, have emerged that provide the means to identify, localize and monitor stem cells longitudinally in vivo following implantation. This Review will examine the various cardiac cellular tracking modalities, including the combinatorial use of several probes in multimodality imaging, with a focus on data from the last five years. PMID:20027188

Students' ideas about prismatic images: teaching experiments for an image-based approach

NASA Astrophysics Data System (ADS)

Grusche, Sascha

2017-05-01

Prismatic refraction is a classic topic in science education. To investigate how undergraduate students think about prismatic dispersion, and to see how they change their thinking when observing dispersed images, five teaching experiments were done and analysed according to the Model of Educational Reconstruction. For projection through a prism, the students used a 'split image projection' conceptualisation. For the view through a prism, this conceptualisation was not fruitful. Based on the observed images, six of seven students changed to a 'diverted image projection' conceptualisation. From a comparison between students' and scientists' ideas, teaching implications are derived for an image-based approach.

The first clinical treatment with kilovoltage intrafraction monitoring (KIM): A real-time image guidance method

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

Keall, Paul J., E-mail: paul.keall@sydney.edu.au; O’Brien, Ricky; Huang, Chen-Yu

Purpose: Kilovoltage intrafraction monitoring (KIM) is a real-time image guidance method that uses widely available radiotherapy technology, i.e., a gantry-mounted x-ray imager. The authors report on the geometric and dosimetric results of the first patient treatment using KIM which occurred on September 16, 2014. Methods: KIM uses current and prior 2D x-ray images to estimate the 3D target position during cancer radiotherapy treatment delivery. KIM software was written to process kilovoltage (kV) images streamed from a standard C-arm linear accelerator with a gantry-mounted kV x-ray imaging system. A 120° pretreatment kV imaging arc was acquired to build the patient-specific 2Dmore » to 3D motion correlation. The kV imager was activated during the megavoltage (MV) treatment, a dual arc VMAT prostate treatment, to estimate the 3D prostate position in real-time. All necessary ethics, legal, and regulatory requirements were met for this clinical study. The quality assurance processes were completed and peer reviewed. Results: During treatment, a prostate position offset of nearly 3 mm in the posterior direction was observed with KIM. This position offset did not trigger a gating event. After the treatment, the prostate motion was independently measured using kV/MV triangulation, resulting in a mean difference of less than 0.6 mm and standard deviation of less than 0.6 mm in each direction. The accuracy of the marker segmentation was visually assessed during and after treatment and found to be performing well. During treatment, there were no interruptions due to performance of the KIM software. Conclusions: For the first time, KIM has been used for real-time image guidance during cancer radiotherapy. The measured accuracy and precision were both submillimeter for the first treatment fraction. This clinical translational research milestone paves the way for the broad implementation of real-time image guidance to facilitate the detection and correction of geometric

Biochemical Imaging of Gliomas Using MR Spectroscopic Imaging for Radiotherapy Treatment Planning

NASA Astrophysics Data System (ADS)

Heikal, Amr Ahmed

This thesis discusses the main obstacles facing wide clinical implementation of magnetic resonance spectroscopic imaging (MRSI) as a tumor delineation tool for radiotherapy treatment planning, particularly for gliomas. These main obstacles are identified as 1. observer bias and poor interpretational reproducibility of the results of MRSI scans, and 2. the long scan times required to conduct MRSI scans. An examination of an existing user-independent MRSI tumor delineation technique known as the choline-to-NAA index (CNI) is conducted to assess its utility in providing a tool for reproducible interpretation of MRSI results. While working with spatial resolutions typically twice those on which the CNI model was originally designed, a region of statistical uncertainty was discovered between the tumor and normal tissue populations and as such a modification to the CNI model was introduced to clearly identify that region. To address the issue of long scan times, a series of studies were conducted to adapt a scan acceleration technique, compressed sensing (CS), to work with MRSI and to quantify the effects of such a novel technique on the modulation transfer function (MTF), an important quantitative imaging metric. The studies included the development of the first phantom based method of measuring the MTF for MRSI data, a study of the correlation between the k-space sampling patterns used for compressed sensing and the resulting MTFs, and the introduction of a technique circumventing some of side-effects of compressed sensing by exploiting the conjugate symmetry property of k-space. The work in this thesis provides two essential steps towards wide clinical implementation of MRSI-based tumor delineation. The proposed modifications to the CNI method coupled with the application of CS to MRSI address the two main obstacles outlined. However, there continues to be room for improvement and questions that need to be answered by future research.

Non-invasive airway health assessment: synchrotron imaging reveals effects of rehydrating treatments on mucociliary transit in-vivo.

PubMed

Donnelley, Martin; Morgan, Kaye S; Siu, Karen K W; Farrow, Nigel R; Stahr, Charlene S; Boucher, Richard C; Fouras, Andreas; Parsons, David W

2014-01-14

To determine the efficacy of potential cystic fibrosis (CF) therapies we have developed a novel mucociliary transit (MCT) measurement that uses synchrotron phase contrast X-ray imaging (PCXI) to non-invasively measure the transit rate of individual micron-sized particles deposited into the airways of live mice. The aim of this study was to image changes in MCT produced by a rehydrating treatment based on hypertonic saline (HS), a current CF clinical treatment. Live mice received HS containing a long acting epithelial sodium channel blocker (P308); isotonic saline; or no treatment, using a nebuliser integrated within a small-animal ventilator circuit. Marker particle motion was tracked for 20 minutes using PCXI. There were statistically significant increases in MCT in the isotonic and HS-P308 groups. The ability to quantify in vivo changes in MCT may have utility in pre-clinical research studies designed to bring new genetic and pharmaceutical treatments for respiratory diseases into clinical trials.

Non-invasive airway health assessment: Synchrotron imaging reveals effects of rehydrating treatments on mucociliary transit in-vivo

NASA Astrophysics Data System (ADS)

Donnelley, Martin; Morgan, Kaye S.; Siu, Karen K. W.; Farrow, Nigel R.; Stahr, Charlene S.; Boucher, Richard C.; Fouras, Andreas; Parsons, David W.

2014-01-01

To determine the efficacy of potential cystic fibrosis (CF) therapies we have developed a novel mucociliary transit (MCT) measurement that uses synchrotron phase contrast X-ray imaging (PCXI) to non-invasively measure the transit rate of individual micron-sized particles deposited into the airways of live mice. The aim of this study was to image changes in MCT produced by a rehydrating treatment based on hypertonic saline (HS), a current CF clinical treatment. Live mice received HS containing a long acting epithelial sodium channel blocker (P308); isotonic saline; or no treatment, using a nebuliser integrated within a small-animal ventilator circuit. Marker particle motion was tracked for 20 minutes using PCXI. There were statistically significant increases in MCT in the isotonic and HS-P308 groups. The ability to quantify in vivo changes in MCT may have utility in pre-clinical research studies designed to bring new genetic and pharmaceutical treatments for respiratory diseases into clinical trials.

Quantum Image Steganography and Steganalysis Based On LSQu-Blocks Image Information Concealing Algorithm

NASA Astrophysics Data System (ADS)

A. AL-Salhi, Yahya E.; Lu, Songfeng

2016-08-01

Quantum steganography can solve some problems that are considered inefficient in image information concealing. It researches on Quantum image information concealing to have been widely exploited in recent years. Quantum image information concealing can be categorized into quantum image digital blocking, quantum image stereography, anonymity and other branches. Least significant bit (LSB) information concealing plays vital roles in the classical world because many image information concealing algorithms are designed based on it. Firstly, based on the novel enhanced quantum representation (NEQR), image uniform blocks clustering around the concrete the least significant Qu-block (LSQB) information concealing algorithm for quantum image steganography is presented. Secondly, a clustering algorithm is proposed to optimize the concealment of important data. Finally, we used Con-Steg algorithm to conceal the clustered image blocks. Information concealing located on the Fourier domain of an image can achieve the security of image information, thus we further discuss the Fourier domain LSQu-block information concealing algorithm for quantum image based on Quantum Fourier Transforms. In our algorithms, the corresponding unitary Transformations are designed to realize the aim of concealing the secret information to the least significant Qu-block representing color of the quantum cover image. Finally, the procedures of extracting the secret information are illustrated. Quantum image LSQu-block image information concealing algorithm can be applied in many fields according to different needs.

Treatment Planning and Image Guidance for Radiofrequency Ablations of Large Tumors

PubMed Central

Ren, Hongliang; Campos-Nanez, Enrique; Yaniv, Ziv; Banovac, Filip; Abeledo, Hernan; Hata, Nobuhiko; Cleary, Kevin

2014-01-01

This article addresses the two key challenges in computer-assisted percutaneous tumor ablation: planning multiple overlapping ablations for large tumors while avoiding critical structures, and executing the prescribed plan. Towards semi-automatic treatment planning for image-guided surgical interventions, we develop a systematic approach to the needle-based ablation placement task, ranging from pre-operative planning algorithms to an intra-operative execution platform. The planning system incorporates clinical constraints on ablations and trajectories using a multiple objective optimization formulation, which consists of optimal path selection and ablation coverage optimization based on integer programming. The system implementation is presented and validated in phantom studies and on an animal model. The presented system can potentially be further extended for other ablation techniques such as cryotherapy. PMID:24235279

Object recognition based on Google's reverse image search and image similarity

NASA Astrophysics Data System (ADS)

Horváth, András.

2015-12-01

Image classification is one of the most challenging tasks in computer vision and a general multiclass classifier could solve many different tasks in image processing. Classification is usually done by shallow learning for predefined objects, which is a difficult task and very different from human vision, which is based on continuous learning of object classes and one requires years to learn a large taxonomy of objects which are not disjunct nor independent. In this paper I present a system based on Google image similarity algorithm and Google image database, which can classify a large set of different objects in a human like manner, identifying related classes and taxonomies.

Blood detection in wireless capsule endoscope images based on salient superpixels.

PubMed

Iakovidis, Dimitris K; Chatzis, Dimitris; Chrysanthopoulos, Panos; Koulaouzidis, Anastasios

2015-08-01

Wireless capsule endoscopy (WCE) enables screening of the gastrointestinal (GI) tract with a miniature, optical endoscope packed within a small swallowable capsule, wirelessly transmitting color images. In this paper we propose a novel method for automatic blood detection in contemporary WCE images. Blood is an alarming indication for the presence of pathologies requiring further treatment. The proposed method is based on a new definition of superpixel saliency. The saliency of superpixels is assessed upon their color, enabling the identification of image regions that are likely to contain blood. The blood patterns are recognized by their color features using a supervised learning machine. Experiments performed on a public dataset using automatically selected first-order statistical features from various color components indicate that the proposed method outperforms state-of-the-art methods.

Image Re-Ranking Based on Topic Diversity.

PubMed

Qian, Xueming; Lu, Dan; Wang, Yaxiong; Zhu, Li; Tang, Yuan Yan; Wang, Meng

2017-08-01

Social media sharing Websites allow users to annotate images with free tags, which significantly contribute to the development of the web image retrieval. Tag-based image search is an important method to find images shared by users in social networks. However, how to make the top ranked result relevant and with diversity is challenging. In this paper, we propose a topic diverse ranking approach for tag-based image retrieval with the consideration of promoting the topic coverage performance. First, we construct a tag graph based on the similarity between each tag. Then, the community detection method is conducted to mine the topic community of each tag. After that, inter-community and intra-community ranking are introduced to obtain the final retrieved results. In the inter-community ranking process, an adaptive random walk model is employed to rank the community based on the multi-information of each topic community. Besides, we build an inverted index structure for images to accelerate the searching process. Experimental results on Flickr data set and NUS-Wide data sets show the effectiveness of the proposed approach.

PlenoPatch: Patch-Based Plenoptic Image Manipulation.

PubMed

Zhang, Fang-Lue; Wang, Jue; Shechtman, Eli; Zhou, Zi-Ye; Shi, Jia-Xin; Hu, Shi-Min

2017-05-01

Patch-based image synthesis methods have been successfully applied for various editing tasks on still images, videos and stereo pairs. In this work we extend patch-based synthesis to plenoptic images captured by consumer-level lenselet-based devices for interactive, efficient light field editing. In our method the light field is represented as a set of images captured from different viewpoints. We decompose the central view into different depth layers, and present it to the user for specifying the editing goals. Given an editing task, our method performs patch-based image synthesis on all affected layers of the central view, and then propagates the edits to all other views. Interaction is done through a conventional 2D image editing user interface that is familiar to novice users. Our method correctly handles object boundary occlusion with semi-transparency, thus can generate more realistic results than previous methods. We demonstrate compelling results on a wide range of applications such as hole-filling, object reshuffling and resizing, changing object depth, light field upscaling and parallax magnification.

Use of an imaging device after nonablative radiofrequency (Pellevé): treatment of periorbital rhytids.

PubMed

Javate, Reynaldo M; Grantoza, Charlene L; Buyucan, Kathleen Faye N

2014-01-01

To use the Canfield Reveal imager in objective photo documentation of the effect of nonablative radiofrequency (Pellevé) treatment on periorbital rhytids. This is a prospective cohort study. Twelve patients underwent 1 to 2 sessions of nonablative radiofrequency (Pellevé) treatment over the periorbital region. aged 30 to 60 years old, minimal tissue laxity, and shallow wrinkle development. Standardized reproducible photographs (left, frontal, right views) with use of the Canfield Reveal imager's superimposition feature were taken of each patient prior, immediately after application, and on 2nd, 4th, 6th, and 8th week follow up. Brow elevation was measured in the pre- and posttreatment photographs with the use of the Canfield Reveal imager and rendered the photographs in 3-dimensional images. Comparison of the pre- and posttreatment photographs taken via the Canfield Reveal imager showed reduction in the wrinkles, smoothening, and tightening of the eyelid and the periorbital tissue. Patients exhibited an average increase of 2.05 mm (p<0.001) of eyebrow lift and 0.98 mm (p<0.001) of superior eyelid crease elevation immediately after treatment. Eight weeks after, average brow elevation was measured at 3.52 mm (p<0.001) and crease elevation at 1.84 mm (p<0.001). The 3-dimensional imaging feature rendered in normal skin tone, and shades of gray showed softening of fine lines and crow's feet after treatment. Furthermore, it also rendered in color relief that highlighted the changes seen with depressions noted to decrease after treatment. The Canfield Reveal imager can be used in the objective photodocumentation of subtle and modest effects of nonablative radiofrequency (Pellevé) treatment to the periorbital region.

An Integrative Object-Based Image Analysis Workflow for Uav Images

NASA Astrophysics Data System (ADS)

Yu, Huai; Yan, Tianheng; Yang, Wen; Zheng, Hong

2016-06-01

In this work, we propose an integrative framework to process UAV images. The overall process can be viewed as a pipeline consisting of the geometric and radiometric corrections, subsequent panoramic mosaicking and hierarchical image segmentation for later Object Based Image Analysis (OBIA). More precisely, we first introduce an efficient image stitching algorithm after the geometric calibration and radiometric correction, which employs a fast feature extraction and matching by combining the local difference binary descriptor and the local sensitive hashing. We then use a Binary Partition Tree (BPT) representation for the large mosaicked panoramic image, which starts by the definition of an initial partition obtained by an over-segmentation algorithm, i.e., the simple linear iterative clustering (SLIC). Finally, we build an object-based hierarchical structure by fully considering the spectral and spatial information of the super-pixels and their topological relationships. Moreover, an optimal segmentation is obtained by filtering the complex hierarchies into simpler ones according to some criterions, such as the uniform homogeneity and semantic consistency. Experimental results on processing the post-seismic UAV images of the 2013 Ya'an earthquake demonstrate the effectiveness and efficiency of our proposed method.

Artificial neural network based gynaecological image-guided adaptive brachytherapy treatment planning correction of intra-fractional organs at risk dose variation.

PubMed

Jaberi, Ramin; Siavashpour, Zahra; Aghamiri, Mahmoud Reza; Kirisits, Christian; Ghaderi, Reza

2017-12-01

Intra-fractional organs at risk (OARs) deformations can lead to dose variation during image-guided adaptive brachytherapy (IGABT). The aim of this study was to modify the final accepted brachytherapy treatment plan to dosimetrically compensate for these intra-fractional organs-applicators position variations and, at the same time, fulfilling the dosimetric criteria. Thirty patients with locally advanced cervical cancer, after external beam radiotherapy (EBRT) of 45-50 Gy over five to six weeks with concomitant weekly chemotherapy, and qualified for intracavitary high-dose-rate (HDR) brachytherapy with tandem-ovoid applicators were selected for this study. Second computed tomography scan was done for each patient after finishing brachytherapy treatment with applicators in situ. Artificial neural networks (ANNs) based models were used to predict intra-fractional OARs dose-volume histogram parameters variations and propose a new final plan. A model was developed to estimate the intra-fractional organs dose variations during gynaecological intracavitary brachytherapy. Also, ANNs were used to modify the final brachytherapy treatment plan to compensate dosimetrically for changes in 'organs-applicators', while maintaining target dose at the original level. There are semi-automatic and fast responding models that can be used in the routine clinical workflow to reduce individually IGABT uncertainties. These models can be more validated by more patients' plans to be able to serve as a clinical tool.

Artificial neural network based gynaecological image-guided adaptive brachytherapy treatment planning correction of intra-fractional organs at risk dose variation

PubMed Central

Jaberi, Ramin; Aghamiri, Mahmoud Reza; Kirisits, Christian; Ghaderi, Reza

2017-01-01

Purpose Intra-fractional organs at risk (OARs) deformations can lead to dose variation during image-guided adaptive brachytherapy (IGABT). The aim of this study was to modify the final accepted brachytherapy treatment plan to dosimetrically compensate for these intra-fractional organs-applicators position variations and, at the same time, fulfilling the dosimetric criteria. Material and methods Thirty patients with locally advanced cervical cancer, after external beam radiotherapy (EBRT) of 45-50 Gy over five to six weeks with concomitant weekly chemotherapy, and qualified for intracavitary high-dose-rate (HDR) brachytherapy with tandem-ovoid applicators were selected for this study. Second computed tomography scan was done for each patient after finishing brachytherapy treatment with applicators in situ. Artificial neural networks (ANNs) based models were used to predict intra-fractional OARs dose-volume histogram parameters variations and propose a new final plan. Results A model was developed to estimate the intra-fractional organs dose variations during gynaecological intracavitary brachytherapy. Also, ANNs were used to modify the final brachytherapy treatment plan to compensate dosimetrically for changes in ‘organs-applicators’, while maintaining target dose at the original level. Conclusions There are semi-automatic and fast responding models that can be used in the routine clinical workflow to reduce individually IGABT uncertainties. These models can be more validated by more patients’ plans to be able to serve as a clinical tool. PMID:29441094

Model-based imaging of cardiac electrical function in human atria

NASA Astrophysics Data System (ADS)

Modre, Robert; Tilg, Bernhard; Fischer, Gerald; Hanser, Friedrich; Messnarz, Bernd; Schocke, Michael F. H.; Kremser, Christian; Hintringer, Florian; Roithinger, Franz

2003-05-01

Noninvasive imaging of electrical function in the human atria is attained by the combination of data from electrocardiographic (ECG) mapping and magnetic resonance imaging (MRI). An anatomical computer model of the individual patient is the basis for our computer-aided diagnosis of cardiac arrhythmias. Three patients suffering from Wolff-Parkinson-White syndrome, from paroxymal atrial fibrillation, and from atrial flutter underwent an electrophysiological study. After successful treatment of the cardiac arrhythmia with invasive catheter technique, pacing protocols with stimuli at several anatomical sites (coronary sinus, left and right pulmonary vein, posterior site of the right atrium, right atrial appendage) were performed. Reconstructed activation time (AT) maps were validated with catheter-based electroanatomical data, with invasively determined pacing sites, and with pacing at anatomical markers. The individual complex anatomical model of the atria of each patient in combination with a high-quality mesh optimization enables accurate AT imaging, resulting in a localization error for the estimated pacing sites within 1 cm. Our findings may have implications for imaging of atrial activity in patients with focal arrhythmias.

T2*-based MR imaging (gradient echo or susceptibility-weighted imaging) in midline and off-midline intracranial germ cell tumors: a pilot study.

PubMed

Morana, Giovanni; Alves, Cesar Augusto; Tortora, Domenico; Finlay, Jonathan L; Severino, Mariasavina; Nozza, Paolo; Ravegnani, Marcello; Pavanello, Marco; Milanaccio, Claudia; Maghnie, Mohamad; Rossi, Andrea; Garrè, Maria Luisa

2018-01-01

The role of T2*-based MR imaging in intracranial germ cell tumors (GCTs) has not been fully elucidated. The aim of this study was to evaluate the susceptibility-weighted imaging (SWI) or T2* gradient echo (GRE) features of germinomas and non-germinomatous germ cell tumors (NGGCTs) in midline and off-midline locations. We retrospectively evaluated all consecutive pediatric patients referred to our institution between 2005 and 2016, for newly diagnosed, treatment-naïve intracranial GCT, who underwent MRI, including T2*-based MR imaging (T2* GRE sequences or SWI). Standard pre- and post-contrast T1- and T2-weighted imaging characteristics along with T2*-based MR imaging features of all lesions were evaluated. Diagnosis was performed in accordance with the SIOP CNS GCT protocol criteria. Twenty-four subjects met the inclusion criteria (17 males and 7 females). There were 17 patients with germinomas, including 5 basal ganglia primaries, and 7 patients with secreting NGGCT. All off-midline germinomas presented with SWI or GRE hypointensity; among midline GCT, all NGGCTs showed SWI or GRE hypointensity whereas all but one pure germinoma were isointense or hyperintense to normal parenchyma. A significant difference emerged on T2*-based MR imaging among midline germinomas, NGGCTs, and off-midline germinomas (p < 0.001). Assessment of the SWI or GRE characteristics of intracranial GCT may potentially assist in differentiating pure germinomas from NGGCT and in the characterization of basal ganglia involvement. T2*-based MR imaging is recommended in case of suspected intracranial GCT.

Assessing paedophilia based on the haemodynamic brain response to face images.

PubMed

Ponseti, Jorge; Granert, Oliver; Van Eimeren, Thilo; Jansen, Olav; Wolff, Stephan; Beier, Klaus; Deuschl, Günther; Huchzermeier, Christian; Stirn, Aglaja; Bosinski, Hartmut; Roman Siebner, Hartwig

2016-01-01

Objective assessment of sexual preferences may be of relevance in the treatment and prognosis of child sexual offenders. Previous research has indicated that this can be achieved by pattern classification of brain responses to sexual child and adult images. Our recent research showed that human face processing is tuned to sexual age preferences. This observation prompted us to test whether paedophilia can be inferred based on the haemodynamic brain responses to adult and child faces. Twenty-four men sexually attracted to prepubescent boys or girls (paedophiles) and 32 men sexually attracted to men or women (teleiophiles) were exposed to images of child and adult, male and female faces during a functional magnetic resonance imaging (fMRI) session. A cross-validated, automatic pattern classification algorithm of brain responses to facial stimuli yielded four misclassified participants (three false positives), corresponding to a specificity of 91% and a sensitivity of 95%. These results indicate that the functional response to facial stimuli can be reliably used for fMRI-based classification of paedophilia, bypassing the problem of showing child sexual stimuli to paedophiles.

Broadband Phase Retrieval for Image-Based Wavefront Sensing

NASA Technical Reports Server (NTRS)

Dean, Bruce H.

2007-01-01

A focus-diverse phase-retrieval algorithm has been shown to perform adequately for the purpose of image-based wavefront sensing when (1) broadband light (typically spanning the visible spectrum) is used in forming the images by use of an optical system under test and (2) the assumption of monochromaticity is applied to the broadband image data. Heretofore, it had been assumed that in order to obtain adequate performance, it is necessary to use narrowband or monochromatic light. Some background information, including definitions of terms and a brief description of pertinent aspects of image-based phase retrieval, is prerequisite to a meaningful summary of the present development. Phase retrieval is a general term used in optics to denote estimation of optical imperfections or aberrations of an optical system under test. The term image-based wavefront sensing refers to a general class of algorithms that recover optical phase information, and phase-retrieval algorithms constitute a subset of this class. In phase retrieval, one utilizes the measured response of the optical system under test to produce a phase estimate. The optical response of the system is defined as the image of a point-source object, which could be a star or a laboratory point source. The phase-retrieval problem is characterized as image-based in the sense that a charge-coupled-device camera, preferably of scientific imaging quality, is used to collect image data where the optical system would normally form an image. In a variant of phase retrieval, denoted phase-diverse phase retrieval [which can include focus-diverse phase retrieval (in which various defocus planes are used)], an additional known aberration (or an equivalent diversity function) is superimposed as an aid in estimating unknown aberrations by use of an image-based wavefront-sensing algorithm. Image-based phase-retrieval differs from such other wavefront-sensing methods, such as interferometry, shearing interferometry, curvature

Applications based on restored satellite images

NASA Astrophysics Data System (ADS)

Arbel, D.; Levin, S.; Nir, M.; Bhasteker, I.

2005-08-01

Satellites orbit the earth and obtain imagery of the ground below. The quality of satellite images is affected by the properties of the atmospheric imaging path, which degrade the image by blurring it and reducing its contrast. Applications involving satellite images are many and varied. Imaging systems are also different technologically and in their physical and optical characteristics such as sensor types, resolution, field of view (FOV), spectral range of the acquiring channels - from the visible to the thermal IR (TIR), platforms (mobilization facilities; aircrafts and/or spacecrafts), altitude above ground surface etc. It is important to obtain good quality satellite images because of the variety of applications based on them. The more qualitative is the recorded image, the more information is yielded from the image. The restoration process is conditioned by gathering much data about the atmospheric medium and its characterization. In return, there is a contribution to the applications based on those restorations i.e., satellite communication, warfare against long distance missiles, geographical aspects, agricultural aspects, economical aspects, intelligence, security, military, etc. Several manners to use restored Landsat 7 enhanced thematic mapper plus (ETM+) satellite images are suggested and presented here. In particular, using the restoration results for few potential geographical applications such as color classification and mapping (roads and streets localization) methods.

Medical Image Tamper Detection Based on Passive Image Authentication.

PubMed

Ulutas, Guzin; Ustubioglu, Arda; Ustubioglu, Beste; V Nabiyev, Vasif; Ulutas, Mustafa

2017-12-01

Telemedicine has gained popularity in recent years. Medical images can be transferred over the Internet to enable the telediagnosis between medical staffs and to make the patient's history accessible to medical staff from anywhere. Therefore, integrity protection of the medical image is a serious concern due to the broadcast nature of the Internet. Some watermarking techniques are proposed to control the integrity of medical images. However, they require embedding of extra information (watermark) into image before transmission. It decreases visual quality of the medical image and can cause false diagnosis. The proposed method uses passive image authentication mechanism to detect the tampered regions on medical images. Structural texture information is obtained from the medical image by using local binary pattern rotation invariant (LBPROT) to make the keypoint extraction techniques more successful. Keypoints on the texture image are obtained with scale invariant feature transform (SIFT). Tampered regions are detected by the method by matching the keypoints. The method improves the keypoint-based passive image authentication mechanism (they do not detect tampering when the smooth region is used for covering an object) by using LBPROT before keypoint extraction because smooth regions also have texture information. Experimental results show that the method detects tampered regions on the medical images even if the forged image has undergone some attacks (Gaussian blurring/additive white Gaussian noise) or the forged regions are scaled/rotated before pasting.

In vivo office-based dynamic imaging of vocal cords in awake patients with swept-source optical coherence tomography

NASA Astrophysics Data System (ADS)

Yu, Lingfeng; Liu, Gangjun; Rubinstein, Marc; Saidi, Arya; Guo, Shuguang; Wong, Brian J. F.; Chen, Zhongping

2009-02-01

Optical coherence tomography (OCT) is an evolving noninvasive imaging modality and has been used to image the human larynx during surgical endoscopy. The design of a long GRIN lens based probe capable of capturing images of the human larynx by use of swept-source OCT during a typical office-based laryngoscopy examination is presented. In vivo OCT imaging of the human larynx is demonstrated with 40 fame/second. Dynamic vibration of the vocal folds is recorded to provide not only high-resolution cross-sectional tissue structures but also vibration parameters, such as the vibration frequency and magnitude of the vocal cord, which provide important information for clinical diagnosis and treatment, as well as in fundamental research of the voice. Office-based OCT is a promising imaging modality to study the larynx.

General imaging of advanced 3D mask objects based on the fully-vectorial extended Nijboer-Zernike (ENZ) theory

NASA Astrophysics Data System (ADS)

van Haver, Sven; Janssen, Olaf T. A.; Braat, Joseph J. M.; Janssen, Augustus J. E. M.; Urbach, H. Paul; Pereira, Silvania F.

2008-03-01

In this paper we introduce a new mask imaging algorithm that is based on the source point integration method (or Abbe method). The method presented here distinguishes itself from existing methods by exploiting the through-focus imaging feature of the Extended Nijboer-Zernike (ENZ) theory of diffraction. An introduction to ENZ-theory and its application in general imaging is provided after which we describe the mask imaging scheme that can be derived from it. The remainder of the paper is devoted to illustrating the advantages of the new method over existing methods (Hopkins-based). To this extent several simulation results are included that illustrate advantages arising from: the accurate incorporation of isolated structures, the rigorous treatment of the object (mask topography) and the fully vectorial through-focus image formation of the ENZ-based algorithm.

DSA Image Blood Vessel Skeleton Extraction Based on Anti-concentration Diffusion and Level Set Method

NASA Astrophysics Data System (ADS)

Xu, Jing; Wu, Jian; Feng, Daming; Cui, Zhiming

Serious types of vascular diseases such as carotid stenosis, aneurysm and vascular malformation may lead to brain stroke, which are the third leading cause of death and the number one cause of disability. In the clinical practice of diagnosis and treatment of cerebral vascular diseases, how to do effective detection and description of the vascular structure of two-dimensional angiography sequence image that is blood vessel skeleton extraction has been a difficult study for a long time. This paper mainly discussed two-dimensional image of blood vessel skeleton extraction based on the level set method, first do the preprocessing to the DSA image, namely uses anti-concentration diffusion model for the effective enhancement and uses improved Otsu local threshold segmentation technology based on regional division for the image binarization, then vascular skeleton extraction based on GMM (Group marching method) with fast sweeping theory was actualized. Experiments show that our approach not only improved the time complexity, but also make a good extraction results.

Virtual reality exposure using three-dimensional images for the treatment of social phobia.

PubMed

Gebara, Cristiane M; Barros-Neto, Tito P de; Gertsenchtein, Leticia; Lotufo-Neto, Francisco

2016-03-01

To test a potential treatment for social phobia, which provides exposure to phobia-inducing situations via computer-generated, three-dimensional images, using an open clinical trial design. Twenty-one patients with a DSM-IV diagnosis of social phobia took part in the trial. Treatment consisted of up to 12 sessions of exposure to relevant images, each session lasting 50 minutes. Improvements in social anxiety were seen in all scales and instruments used, including at follow-up 6 months after the end of treatment. The average number of sessions was seven, as the participants habituated rapidly to the process. Only one participant dropped out. This study provides evidence that exposure to computer-generated three-dimensional images is relatively inexpensive, leads to greater treatment adherence, and can reduce social anxiety. Further studies are needed to corroborate these findings.

Big data in multiple sclerosis: development of a web-based longitudinal study viewer in an imaging informatics-based eFolder system for complex data analysis and management

NASA Astrophysics Data System (ADS)

Ma, Kevin; Wang, Ximing; Lerner, Alex; Shiroishi, Mark; Amezcua, Lilyana; Liu, Brent

2015-03-01

In the past, we have developed and displayed a multiple sclerosis eFolder system for patient data storage, image viewing, and automatic lesion quantification results stored in DICOM-SR format. The web-based system aims to be integrated in DICOM-compliant clinical and research environments to aid clinicians in patient treatments and disease tracking. This year, we have further developed the eFolder system to handle big data analysis and data mining in today's medical imaging field. The database has been updated to allow data mining and data look-up from DICOM-SR lesion analysis contents. Longitudinal studies are tracked, and any changes in lesion volumes and brain parenchyma volumes are calculated and shown on the webbased user interface as graphical representations. Longitudinal lesion characteristic changes are compared with patients' disease history, including treatments, symptom progressions, and any other changes in the disease profile. The image viewer is updated such that imaging studies can be viewed side-by-side to allow visual comparisons. We aim to use the web-based medical imaging informatics eFolder system to demonstrate big data analysis in medical imaging, and use the analysis results to predict MS disease trends and patterns in Hispanic and Caucasian populations in our pilot study. The discovery of disease patterns among the two ethnicities is a big data analysis result that will help lead to personalized patient care and treatment planning.

Fluorescent marker-based and marker-free discrimination between healthy and cancerous human tissues using hyper-spectral imaging

NASA Astrophysics Data System (ADS)

Arnold, Thomas; De Biasio, Martin; Leitner, Raimund

2015-06-01

Two problems are addressed in this paper (i) the fluorescent marker-based and the (ii) marker-free discrimination between healthy and cancerous human tissues. For both applications the performance of hyper-spectral methods are quantified. Fluorescent marker-based tissue classification uses a number of fluorescent markers to dye specific parts of a human cell. The challenge is that the emission spectra of the fluorescent dyes overlap considerably. They are, furthermore disturbed by the inherent auto-fluorescence of human tissue. This results in ambiguities and decreased image contrast causing difficulties for the treatment decision. The higher spectral resolution introduced by tunable-filter-based spectral imaging in combination with spectral unmixing techniques results in an improvement of the image contrast and therefore more reliable information for the physician to choose the treatment decision. Marker-free tissue classification is based solely on the subtle spectral features of human tissue without the use of artificial markers. The challenge in this case is that the spectral differences between healthy and cancerous tissues are subtle and embedded in intra- and inter-patient variations of these features. The contributions of this paper are (i) the evaluation of hyper-spectral imaging in combination with spectral unmixing techniques for fluorescence marker-based tissue classification, (ii) the evaluation of spectral imaging for marker-free intra surgery tissue classification. Within this paper, we consider real hyper-spectral fluorescence and endoscopy data sets to emphasize the practical capability of the proposed methods. It is shown that the combination of spectral imaging with multivariate statistical methods can improve the sensitivity and specificity of the detection and the staging of cancerous tissues compared to standard procedures.

HCS-Neurons: identifying phenotypic changes in multi-neuron images upon drug treatments of high-content screening.

PubMed

Charoenkwan, Phasit; Hwang, Eric; Cutler, Robert W; Lee, Hua-Chin; Ko, Li-Wei; Huang, Hui-Ling; Ho, Shinn-Ying

2013-01-01

High-content screening (HCS) has become a powerful tool for drug discovery. However, the discovery of drugs targeting neurons is still hampered by the inability to accurately identify and quantify the phenotypic changes of multiple neurons in a single image (named multi-neuron image) of a high-content screen. Therefore, it is desirable to develop an automated image analysis method for analyzing multi-neuron images. We propose an automated analysis method with novel descriptors of neuromorphology features for analyzing HCS-based multi-neuron images, called HCS-neurons. To observe multiple phenotypic changes of neurons, we propose two kinds of descriptors which are neuron feature descriptor (NFD) of 13 neuromorphology features, e.g., neurite length, and generic feature descriptors (GFDs), e.g., Haralick texture. HCS-neurons can 1) automatically extract all quantitative phenotype features in both NFD and GFDs, 2) identify statistically significant phenotypic changes upon drug treatments using ANOVA and regression analysis, and 3) generate an accurate classifier to group neurons treated by different drug concentrations using support vector machine and an intelligent feature selection method. To evaluate HCS-neurons, we treated P19 neurons with nocodazole (a microtubule depolymerizing drug which has been shown to impair neurite development) at six concentrations ranging from 0 to 1000 ng/mL. The experimental results show that all the 13 features of NFD have statistically significant difference with respect to changes in various levels of nocodazole drug concentrations (NDC) and the phenotypic changes of neurites were consistent to the known effect of nocodazole in promoting neurite retraction. Three identified features, total neurite length, average neurite length, and average neurite area were able to achieve an independent test accuracy of 90.28% for the six-dosage classification problem. This NFD module and neuron image datasets are provided as a freely downloadable

Medical image analysis of knee joint lipoma arborescens and arthroscopic treatment.

PubMed

Zhu, Guangyu; Tian, Xiangdong; Du, Dongfeng; Lei, Ming; Guan, Lei; Wang, Jian; Tan, Yetong; Yang, Chen; Zheng, Xinxin

2018-06-01

Arthroscopy is a minimally invasive surgical procedure on a joint in which examination and treatment of knee damage is performed using a surgical device known as the arthroscope. Lipoma arborescens (LA), an infrequent intra-articular lesion, originates from mature adipose cells under subsynovial tissue. The synovial membrane is pale yellow with large villous projections. It is caused by various underlying factors. We found many patients with LA and processed them appropriately.The research was implemented to investigate therapeutic effect of semi-automated arthroscopic diagnosis and treatment for knee joint. We used the Stryker arthroscopic in surgery that is 4 mm in diameter with angle at 30°. Patients were chosen by biomechanical analysis and scanning mode. All of the patients underwent radiographic imaging examination, Magnetic Resonance Imaging (MRI), Lysholm Score and Visual Analogue Scale (VAS). Arthroscopic limited synovectomy was carried out on these patients. The wound of all patients healed up. The content of follow-up includes: chief complaints, range of motion of knee joint, Visual Analogue Scale (VAS) and Lysholm score. No swollen nor effusion of the infected knee was found in all patients during the follow-up. The postoperative symptom was markedly alleviated in fourteen patients and partially alleviated in one. All patients were satisfied with the therapeutic effect. We performed biomechanical analysis based on knee slight flexion and extension. Arthroscopy is an endoscope for the diagnosis and treatment of joint diseases. Semi-automated arthroscopic debridement is good for early and mid-term osteoarthritis with Lipoma arborescens. Copyright © 2018. Published by Elsevier Ltd.

High Resolution PET Imaging Probe for the Detection, Molecular Characterization and Treatment Monitoring of Prostate Cancer

DTIC Science & Technology

2010-07-01

W81XWH-09-1-0420 TITLE: High Resolution PET Imaging Probe for the Detection, Molecular Characterization and Treatment Monitoring of Prostate Cancer...4. TITLE AND SUBTITLE High-Resolution PET Imaging Probe for the Detection, Molecular Characterization and Treatment of Prostate Cancer... molecular imaging for diagnosis as well as treatment planning and monitoring in prostate cancer. This investigation hypothesizes that a dedicated

MRI-based treatment planning with pseudo CT generated through atlas registration.

PubMed

Uh, Jinsoo; Merchant, Thomas E; Li, Yimei; Li, Xingyu; Hua, Chiaho

2014-05-01

To evaluate the feasibility and accuracy of magnetic resonance imaging (MRI)-based treatment planning using pseudo CTs generated through atlas registration. A pseudo CT, providing electron density information for dose calculation, was generated by deforming atlas CT images previously acquired on other patients. The authors tested 4 schemes of synthesizing a pseudo CT from single or multiple deformed atlas images: use of a single arbitrarily selected atlas, arithmetic mean process using 6 atlases, and pattern recognition with Gaussian process (PRGP) using 6 or 12 atlases. The required deformation for atlas CT images was derived from a nonlinear registration of conjugated atlas MR images to that of the patient of interest. The contrasts of atlas MR images were adjusted by histogram matching to reduce the effect of different sets of acquisition parameters. For comparison, the authors also tested a simple scheme assigning the Hounsfield unit of water to the entire patient volume. All pseudo CT generating schemes were applied to 14 patients with common pediatric brain tumors. The image similarity of real patient-specific CT and pseudo CTs constructed by different schemes was compared. Differences in computation times were also calculated. The real CT in the treatment planning system was replaced with the pseudo CT, and the dose distribution was recalculated to determine the difference. The atlas approach generally performed better than assigning a bulk CT number to the entire patient volume. Comparing atlas-based schemes, those using multiple atlases outperformed the single atlas scheme. For multiple atlas schemes, the pseudo CTs were similar to the real CTs (correlation coefficient, 0.787-0.819). The calculated dose distribution was in close agreement with the original dose. Nearly the entire patient volume (98.3%-98.7%) satisfied the criteria of chi-evaluation (<2% maximum dose and 2 mm range). The dose to 95% of the volume and the percentage of volume receiving at

MRI-based treatment planning with pseudo CT generated through atlas registration

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

Uh, Jinsoo, E-mail: jinsoo.uh@stjude.org; Merchant, Thomas E.; Hua, Chiaho

2014-05-15

Purpose: To evaluate the feasibility and accuracy of magnetic resonance imaging (MRI)-based treatment planning using pseudo CTs generated through atlas registration. Methods: A pseudo CT, providing electron density information for dose calculation, was generated by deforming atlas CT images previously acquired on other patients. The authors tested 4 schemes of synthesizing a pseudo CT from single or multiple deformed atlas images: use of a single arbitrarily selected atlas, arithmetic mean process using 6 atlases, and pattern recognition with Gaussian process (PRGP) using 6 or 12 atlases. The required deformation for atlas CT images was derived from a nonlinear registration ofmore » conjugated atlas MR images to that of the patient of interest. The contrasts of atlas MR images were adjusted by histogram matching to reduce the effect of different sets of acquisition parameters. For comparison, the authors also tested a simple scheme assigning the Hounsfield unit of water to the entire patient volume. All pseudo CT generating schemes were applied to 14 patients with common pediatric brain tumors. The image similarity of real patient-specific CT and pseudo CTs constructed by different schemes was compared. Differences in computation times were also calculated. The real CT in the treatment planning system was replaced with the pseudo CT, and the dose distribution was recalculated to determine the difference. Results: The atlas approach generally performed better than assigning a bulk CT number to the entire patient volume. Comparing atlas-based schemes, those using multiple atlases outperformed the single atlas scheme. For multiple atlas schemes, the pseudo CTs were similar to the real CTs (correlation coefficient, 0.787–0.819). The calculated dose distribution was in close agreement with the original dose. Nearly the entire patient volume (98.3%–98.7%) satisfied the criteria of chi-evaluation (<2% maximum dose and 2 mm range). The dose to 95% of the volume and

MRI-based treatment planning with pseudo CT generated through atlas registration

PubMed Central

Uh, Jinsoo; Merchant, Thomas E.; Li, Yimei; Li, Xingyu; Hua, Chiaho

2014-01-01

Purpose: To evaluate the feasibility and accuracy of magnetic resonance imaging (MRI)-based treatment planning using pseudo CTs generated through atlas registration. Methods: A pseudo CT, providing electron density information for dose calculation, was generated by deforming atlas CT images previously acquired on other patients. The authors tested 4 schemes of synthesizing a pseudo CT from single or multiple deformed atlas images: use of a single arbitrarily selected atlas, arithmetic mean process using 6 atlases, and pattern recognition with Gaussian process (PRGP) using 6 or 12 atlases. The required deformation for atlas CT images was derived from a nonlinear registration of conjugated atlas MR images to that of the patient of interest. The contrasts of atlas MR images were adjusted by histogram matching to reduce the effect of different sets of acquisition parameters. For comparison, the authors also tested a simple scheme assigning the Hounsfield unit of water to the entire patient volume. All pseudo CT generating schemes were applied to 14 patients with common pediatric brain tumors. The image similarity of real patient-specific CT and pseudo CTs constructed by different schemes was compared. Differences in computation times were also calculated. The real CT in the treatment planning system was replaced with the pseudo CT, and the dose distribution was recalculated to determine the difference. Results: The atlas approach generally performed better than assigning a bulk CT number to the entire patient volume. Comparing atlas-based schemes, those using multiple atlases outperformed the single atlas scheme. For multiple atlas schemes, the pseudo CTs were similar to the real CTs (correlation coefficient, 0.787–0.819). The calculated dose distribution was in close agreement with the original dose. Nearly the entire patient volume (98.3%–98.7%) satisfied the criteria of chi-evaluation (<2% maximum dose and 2 mm range). The dose to 95% of the volume and the

Content-based image retrieval with ontological ranking

NASA Astrophysics Data System (ADS)

Tsai, Shen-Fu; Tsai, Min-Hsuan; Huang, Thomas S.

2010-02-01

Images are a much more powerful medium of expression than text, as the adage says: "One picture is worth a thousand words." It is because compared with text consisting of an array of words, an image has more degrees of freedom and therefore a more complicated structure. However, the less limited structure of images presents researchers in the computer vision community a tough task of teaching machines to understand and organize images, especially when a limit number of learning examples and background knowledge are given. The advance of internet and web technology in the past decade has changed the way human gain knowledge. People, hence, can exchange knowledge with others by discussing and contributing information on the web. As a result, the web pages in the internet have become a living and growing source of information. One is therefore tempted to wonder whether machines can learn from the web knowledge base as well. Indeed, it is possible to make computer learn from the internet and provide human with more meaningful knowledge. In this work, we explore this novel possibility on image understanding applied to semantic image search. We exploit web resources to obtain links from images to keywords and a semantic ontology constituting human's general knowledge. The former maps visual content to related text in contrast to the traditional way of associating images with surrounding text; the latter provides relations between concepts for machines to understand to what extent and in what sense an image is close to the image search query. With the aid of these two tools, the resulting image search system is thus content-based and moreover, organized. The returned images are ranked and organized such that semantically similar images are grouped together and given a rank based on the semantic closeness to the input query. The novelty of the system is twofold: first, images are retrieved not only based on text cues but their actual contents as well; second, the grouping

An effective content-based image retrieval technique for image visuals representation based on the bag-of-visual-words model.

PubMed

Jabeen, Safia; Mehmood, Zahid; Mahmood, Toqeer; Saba, Tanzila; Rehman, Amjad; Mahmood, Muhammad Tariq

2018-01-01

For the last three decades, content-based image retrieval (CBIR) has been an active research area, representing a viable solution for retrieving similar images from an image repository. In this article, we propose a novel CBIR technique based on the visual words fusion of speeded-up robust features (SURF) and fast retina keypoint (FREAK) feature descriptors. SURF is a sparse descriptor whereas FREAK is a dense descriptor. Moreover, SURF is a scale and rotation-invariant descriptor that performs better in the case of repeatability, distinctiveness, and robustness. It is robust to noise, detection errors, geometric, and photometric deformations. It also performs better at low illumination within an image as compared to the FREAK descriptor. In contrast, FREAK is a retina-inspired speedy descriptor that performs better for classification-based problems as compared to the SURF descriptor. Experimental results show that the proposed technique based on the visual words fusion of SURF-FREAK descriptors combines the features of both descriptors and resolves the aforementioned issues. The qualitative and quantitative analysis performed on three image collections, namely Corel-1000, Corel-1500, and Caltech-256, shows that proposed technique based on visual words fusion significantly improved the performance of the CBIR as compared to the feature fusion of both descriptors and state-of-the-art image retrieval techniques.

Development of a software based automatic exposure control system for use in image guided radiation therapy

NASA Astrophysics Data System (ADS)

Morton, Daniel R.

Modern image guided radiation therapy involves the use of an isocentrically mounted imaging system to take radiographs of a patient's position before the start of each treatment. Image guidance helps to minimize errors associated with a patients setup, but the radiation dose received by patients from imaging must be managed to ensure no additional risks. The Varian On-Board Imager (OBI) (Varian Medical Systems, Inc., Palo Alto, CA) does not have an automatic exposure control system and therefore requires exposure factors to be manually selected. Without patient specific exposure factors, images may become saturated and require multiple unnecessary exposures. A software based automatic exposure control system has been developed to predict optimal, patient specific exposure factors. The OBI system was modelled in terms of the x-ray tube output and detector response in order to calculate the level of detector saturation for any exposure situation. Digitally reconstructed radiographs are produced via ray-tracing through the patients' volumetric datasets that are acquired for treatment planning. The ray-trace determines the attenuation of the patient and subsequent x-ray spectra incident on the imaging detector. The resulting spectra are used in the detector response model to determine the exposure levels required to minimize detector saturation. Images calculated for various phantoms showed good agreement with the images that were acquired on the OBI. Overall, regions of detector saturation were accurately predicted and the detector response for non-saturated regions in images of an anthropomorphic phantom were calculated to generally be within 5 to 10 % of the measured values. Calculations were performed on patient data and found similar results as the phantom images, with the calculated images being able to determine detector saturation with close agreement to images that were acquired during treatment. Overall, it was shown that the system model and calculation

Multimodality molecular imaging and extracellular vesicle release based genetic profiling with porphyrin nanodroplets (Conference Presentation)

NASA Astrophysics Data System (ADS)

Zemp, Roger J.; Paproski, Robert J.

2017-03-01

For emerging tissue-engineering applications, transplants, and cell-based therapies it is important to assess cell viability and function in vivo in deep tissues. Bioluminescence and fluorescence methods are poorly suited to deep monitoring applications with high resolution and require genetically-engineered reporters which are not always feasible. We report on a method for imaging cell viability using deep, high-resolution photoacoustic imaging. We use an exogenous dye, Resazurin, itself weakly fluorescent until it is reduced from blue to a pink color with bright red fluorescence. Upon cell death fluorescence is lost and an absorption shift is observed. The irreversible reaction of resazurin to resorufin is proportional to aerobic respiration. We detect colorimetric absorption shifts using multispectral photoacoustic imaging and quantify the fraction of viable cells. SKOV-3 cells with and without ±80oC heat treatment were imaged after Resazurin treatment. High 575nm:620nm ratiometric absorption and photoacoustic signals in viable cells were observed with a much lower ratio in low-viability populations.

Use of electronic portal imaging devices for electron treatment verification.

PubMed

Kairn, T; Aland, T; Crowe, S B; Trapp, J V

2016-03-01

This study aims to help broaden the use of electronic portal imaging devices (EPIDs) for pre-treatment patient positioning verification, from photon-beam radiotherapy to photon- and electron-beam radiotherapy, by proposing and testing a method for acquiring clinically-useful EPID images of patient anatomy using electron beams, with a view to enabling and encouraging further research in this area. EPID images used in this study were acquired using all available beams from a linac configured to deliver electron beams with nominal energies of 6, 9, 12, 16 and 20 MeV, as well as photon beams with nominal energies of 6 and 10 MV. A widely-available heterogeneous, approximately-humanoid, thorax phantom was used, to provide an indication of the contrast and noise produced when imaging different types of tissue with comparatively realistic thicknesses. The acquired images were automatically calibrated, corrected for the effects of variations in the sensitivity of individual photodiodes, using a flood field image. For electron beam imaging, flood field EPID calibration images were acquired with and without the placement of blocks of water-equivalent plastic (with thicknesses approximately equal to the practical range of electrons in the plastic) placed upstream of the EPID, to filter out the primary electron beam, leaving only the bremsstrahlung photon signal. While the electron beam images acquired using a standard (unfiltered) flood field calibration were observed to be noisy and difficult to interpret, the electron beam images acquired using the filtered flood field calibration showed tissues and bony anatomy with levels of contrast and noise that were similar to the contrast and noise levels seen in the clinically acceptable photon beam EPID images. The best electron beam imaging results (highest contrast, signal-to-noise and contrast-to-noise ratios) were achieved when the images were acquired using the higher energy electron beams (16 and 20 MeV) when the EPID was

Image intensifier-based volume tomographic angiography imaging system: system evaluation

NASA Astrophysics Data System (ADS)

Ning, Ruola; Wang, Xiaohui; Shen, Jianjun; Conover, David L.

1995-05-01

An image intensifier-based rotational volume tomographic angiography imaging system has been constructed. The system consists of an x-ray tube and an image intensifier that are separately mounted on a gantry. This system uses an image intensifier coupled to a TV camera as a two-dimensional detector so that a set of two-dimensional projections can be acquired for a direct three-dimensional reconstruction (3D). This system has been evaluated with two phantoms: a vascular phantom and a monkey head cadaver. One hundred eighty projections of each phantom were acquired with the system. A set of three-dimensional images were directly reconstructed from the projection data. The experimental results indicate that good imaging quality can be obtained with this system.

Application of Multimodality Imaging Fusion Technology in Diagnosis and Treatment of Malignant Tumors under the Precision Medicine Plan.

PubMed

Wang, Shun-Yi; Chen, Xian-Xia; Li, Yi; Zhang, Yu-Ying

2016-12-20

The arrival of precision medicine plan brings new opportunities and challenges for patients undergoing precision diagnosis and treatment of malignant tumors. With the development of medical imaging, information on different modality imaging can be integrated and comprehensively analyzed by imaging fusion system. This review aimed to update the application of multimodality imaging fusion technology in the precise diagnosis and treatment of malignant tumors under the precision medicine plan. We introduced several multimodality imaging fusion technologies and their application to the diagnosis and treatment of malignant tumors in clinical practice. The data cited in this review were obtained mainly from the PubMed database from 1996 to 2016, using the keywords of "precision medicine", "fusion imaging", "multimodality", and "tumor diagnosis and treatment". Original articles, clinical practice, reviews, and other relevant literatures published in English were reviewed. Papers focusing on precision medicine, fusion imaging, multimodality, and tumor diagnosis and treatment were selected. Duplicated papers were excluded. Multimodality imaging fusion technology plays an important role in tumor diagnosis and treatment under the precision medicine plan, such as accurate location, qualitative diagnosis, tumor staging, treatment plan design, and real-time intraoperative monitoring. Multimodality imaging fusion systems could provide more imaging information of tumors from different dimensions and angles, thereby offing strong technical support for the implementation of precision oncology. Under the precision medicine plan, personalized treatment of tumors is a distinct possibility. We believe that multimodality imaging fusion technology will find an increasingly wide application in clinical practice.

Developing stereo image based robot control system

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

Suprijadi,; Pambudi, I. R.; Woran, M.

Application of image processing is developed in various field and purposes. In the last decade, image based system increase rapidly with the increasing of hardware and microprocessor performance. Many fields of science and technology were used this methods especially in medicine and instrumentation. New technique on stereovision to give a 3-dimension image or movie is very interesting, but not many applications in control system. Stereo image has pixel disparity information that is not existed in single image. In this research, we proposed a new method in wheel robot control system using stereovision. The result shows robot automatically moves based onmore » stereovision captures.« less

Three dimensional image correlation of CT, MR, and PET studies in radiotherapy treatment planning of brain tumors.

PubMed

Schad, L R; Boesecke, R; Schlegel, W; Hartmann, G H; Sturm, V; Strauss, L G; Lorenz, W J

1987-01-01

A treatment planning system for stereotactic convergent beam irradiation of deeply localized brain tumors is reported. The treatment technique consists of several moving field irradiations in noncoplanar planes at a linear accelerator facility. Using collimated narrow beams, a high concentration of dose within small volumes with a dose gradient of 10-15%/mm was obtained. The dose calculation was based on geometrical information of multiplanar CT or magnetic resonance (MR) imaging data. The patient's head was fixed in a stereotactic localization system, which is usable at CT, MR, and positron emission tomography (PET) installations. Special computer programs for correction of the geometrical MR distortions allowed a precise correlation of the different imaging modalities. The therapist can use combinations of CT, MR, and PET data for defining target volume. For instance, the superior soft tissue contrast of MR coupled with the metabolic features of PET may be a useful addition in the radiation treatment planning process. Furthermore, other features such as calculated dose distribution to critical structures can also be transferred from one set of imaging data to another and can be displayed as three-dimensional shaded structures.

D Reconstruction from Uav-Based Hyperspectral Images

NASA Astrophysics Data System (ADS)

Liu, L.; Xu, L.; Peng, J.

2018-04-01

Reconstructing the 3D profile from a set of UAV-based images can obtain hyperspectral information, as well as the 3D coordinate of any point on the profile. Our images are captured from the Cubert UHD185 (UHD) hyperspectral camera, which is a new type of high-speed onboard imaging spectrometer. And it can get both hyperspectral image and panchromatic image simultaneously. The panchromatic image have a higher spatial resolution than hyperspectral image, but each hyperspectral image provides considerable information on the spatial spectral distribution of the object. Thus there is an opportunity to derive a high quality 3D point cloud from panchromatic image and considerable spectral information from hyperspectral image. The purpose of this paper is to introduce our processing chain that derives a database which can provide hyperspectral information and 3D position of each point. First, We adopt a free and open-source software, Visual SFM which is based on structure from motion (SFM) algorithm, to recover 3D point cloud from panchromatic image. And then get spectral information of each point from hyperspectral image by a self-developed program written in MATLAB. The production can be used to support further research and applications.

Computational polarization difference underwater imaging based on image fusion

NASA Astrophysics Data System (ADS)

Han, Hongwei; Zhang, Xiaohui; Guan, Feng

2016-01-01

Polarization difference imaging can improve the quality of images acquired underwater, whether the background and veiling light are unpolarized or partial polarized. Computational polarization difference imaging technique which replaces the mechanical rotation of polarization analyzer and shortens the time spent to select the optimum orthogonal ǁ and ⊥axes is the improvement of the conventional PDI. But it originally gets the output image by setting the weight coefficient manually to an identical constant for all pixels. In this paper, a kind of algorithm is proposed to combine the Q and U parameters of the Stokes vector through pixel-level image fusion theory based on non-subsample contourlet transform. The experimental system built by the green LED array with polarizer to illuminate a piece of flat target merged in water and the CCD with polarization analyzer to obtain target image under different angle is used to verify the effect of the proposed algorithm. The results showed that the output processed by our algorithm could show more details of the flat target and had higher contrast compared to original computational polarization difference imaging.

Atlas-guided generation of pseudo-CT images for MRI-only and hybrid PET-MRI-guided radiotherapy treatment planning.

PubMed

Arabi, Hossein; Koutsouvelis, Nikolaos; Rouzaud, Michel; Miralbell, Raymond; Zaidi, Habib

2016-09-07

Magnetic resonance imaging (MRI)-guided attenuation correction (AC) of positron emission tomography (PET) data and/or radiation therapy (RT) treatment planning is challenged by the lack of a direct link between MRI voxel intensities and electron density. Therefore, even if this is not a trivial task, a pseudo-computed tomography (CT) image must be predicted from MRI alone. In this work, we propose a two-step (segmentation and fusion) atlas-based algorithm focusing on bone tissue identification to create a pseudo-CT image from conventional MRI sequences and evaluate its performance against the conventional MRI segmentation technique and a recently proposed multi-atlas approach. The clinical studies consisted of pelvic CT, PET and MRI scans of 12 patients with loco-regionally advanced rectal disease. In the first step, bone segmentation of the target image is optimized through local weighted atlas voting. The obtained bone map is then used to assess the quality of deformed atlases to perform voxel-wise weighted atlas fusion. To evaluate the performance of the method, a leave-one-out cross-validation (LOOCV) scheme was devised to find optimal parameters for the model. Geometric evaluation of the produced pseudo-CT images and quantitative analysis of the accuracy of PET AC were performed. Moreover, a dosimetric evaluation of volumetric modulated arc therapy photon treatment plans calculated using the different pseudo-CT images was carried out and compared to those produced using CT images serving as references. The pseudo-CT images produced using the proposed method exhibit bone identification accuracy of 0.89 based on the Dice similarity metric compared to 0.75 achieved by the other atlas-based method. The superior bone extraction resulted in a mean standard uptake value bias of  -1.5  ±  5.0% (mean  ±  SD) in bony structures compared to  -19.9  ±  11.8% and  -8.1  ±  8.2% achieved by MRI segmentation-based (water

Atlas-guided generation of pseudo-CT images for MRI-only and hybrid PET-MRI-guided radiotherapy treatment planning

NASA Astrophysics Data System (ADS)

Arabi, Hossein; Koutsouvelis, Nikolaos; Rouzaud, Michel; Miralbell, Raymond; Zaidi, Habib

2016-09-01

Magnetic resonance imaging (MRI)-guided attenuation correction (AC) of positron emission tomography (PET) data and/or radiation therapy (RT) treatment planning is challenged by the lack of a direct link between MRI voxel intensities and electron density. Therefore, even if this is not a trivial task, a pseudo-computed tomography (CT) image must be predicted from MRI alone. In this work, we propose a two-step (segmentation and fusion) atlas-based algorithm focusing on bone tissue identification to create a pseudo-CT image from conventional MRI sequences and evaluate its performance against the conventional MRI segmentation technique and a recently proposed multi-atlas approach. The clinical studies consisted of pelvic CT, PET and MRI scans of 12 patients with loco-regionally advanced rectal disease. In the first step, bone segmentation of the target image is optimized through local weighted atlas voting. The obtained bone map is then used to assess the quality of deformed atlases to perform voxel-wise weighted atlas fusion. To evaluate the performance of the method, a leave-one-out cross-validation (LOOCV) scheme was devised to find optimal parameters for the model. Geometric evaluation of the produced pseudo-CT images and quantitative analysis of the accuracy of PET AC were performed. Moreover, a dosimetric evaluation of volumetric modulated arc therapy photon treatment plans calculated using the different pseudo-CT images was carried out and compared to those produced using CT images serving as references. The pseudo-CT images produced using the proposed method exhibit bone identification accuracy of 0.89 based on the Dice similarity metric compared to 0.75 achieved by the other atlas-based method. The superior bone extraction resulted in a mean standard uptake value bias of  -1.5  ±  5.0% (mean  ±  SD) in bony structures compared to  -19.9  ±  11.8% and  -8.1  ±  8.2% achieved by MRI segmentation-based (water

Novel fiber optic-based needle redox imager for cancer diagnosis

NASA Astrophysics Data System (ADS)

Kanniyappan, Udayakumar; Xu, He N.; Tang, Qinggong; Gaitan, Brandon; Liu, Yi; Li, Lin Z.; Chen, Yu

2018-02-01

Despite various technological advancements in cancer diagnosis, the mortality rates were not decreased significantly. We aim to develop a novel optical imaging tool to assist cancer diagnosis effectively. Fluorescence spectroscopy/imaging is a fast, rapid, and minimally invasive technique which has been successfully applied to diagnosing cancerous cells/tissues. Recently, the ratiometric imaging of intrinsic fluorescence of reduced nicotinamide adenine dinucleotide (NADH) and flavin adenine dinucleotide (FAD), as pioneered by Britton Chance and the co-workers in 1950-70's, has gained much attention to quantify the physiological parameters of living cells/tissues. The redox ratio, i.e., FAD/(FAD+NADH) or FAD/NADH, has been shown to be sensitive to various metabolic changes in in vivo and in vitro cells/tissues. Optical redox imaging has also been investigated for providing potential imaging biomarkers for cancer transformation, aggressiveness, and treatment response. Towards this goal, we have designed and developed a novel fiberoptic-based needle redox imager (NRI) that can fit into an 11G clinical coaxial biopsy needle for real time imaging during clinical cancer surgery. In the present study, the device is calibrated with tissue mimicking phantoms of FAD and NADH along with various technical parameters such as sensitivity, dynamic range, linearity, and spatial resolution of the system. We also conducted preliminary imaging of tissues ex vivo for validation. We plan to test the NRI on clinical breast cancer patients. Once validated this device may provide an effective tool for clinical cancer diagnosis.

Can state-of-the-art HVS-based objective image quality criteria be used for image reconstruction techniques based on ROI analysis?

NASA Astrophysics Data System (ADS)

Dostal, P.; Krasula, L.; Klima, M.

2012-06-01

Various image processing techniques in multimedia technology are optimized using visual attention feature of the human visual system. Spatial non-uniformity causes that different locations in an image are of different importance in terms of perception of the image. In other words, the perceived image quality depends mainly on the quality of important locations known as regions of interest. The performance of such techniques is measured by subjective evaluation or objective image quality criteria. Many state-of-the-art objective metrics are based on HVS properties; SSIM, MS-SSIM based on image structural information, VIF based on the information that human brain can ideally gain from the reference image or FSIM utilizing the low-level features to assign the different importance to each location in the image. But still none of these objective metrics utilize the analysis of regions of interest. We solve the question if these objective metrics can be used for effective evaluation of images reconstructed by processing techniques based on ROI analysis utilizing high-level features. In this paper authors show that the state-of-the-art objective metrics do not correlate well with subjective evaluation while the demosaicing based on ROI analysis is used for reconstruction. The ROI were computed from "ground truth" visual attention data. The algorithm combining two known demosaicing techniques on the basis of ROI location is proposed to reconstruct the ROI in fine quality while the rest of image is reconstructed with low quality. The color image reconstructed by this ROI approach was compared with selected demosaicing techniques by objective criteria and subjective testing. The qualitative comparison of the objective and subjective results indicates that the state-of-the-art objective metrics are still not suitable for evaluation image processing techniques based on ROI analysis and new criteria is demanded.

Tumor characterization and treatment monitoring of postsurgical human breast specimens using harmonic motion imaging (HMI).

PubMed

Han, Yang; Wang, Shutao; Hibshoosh, Hanina; Taback, Bret; Konofagou, Elisa

2016-05-09

High-intensity focused ultrasound (HIFU) is a noninvasive technique used in the treatment of early-stage breast cancer and benign tumors. To facilitate its translation to the clinic, there is a need for a simple, cost-effective device that can reliably monitor HIFU treatment. We have developed harmonic motion imaging (HMI), which can be used seamlessly in conjunction with HIFU for tumor ablation monitoring, namely harmonic motion imaging for focused ultrasound (HMIFU). The overall objective of this study was to develop an all ultrasound-based system for real-time imaging and ablation monitoring in the human breast in vivo. HMI was performed in 36 specimens (19 normal, 15 invasive ductal carcinomas, and 2 fibroadenomas) immediately after surgical removal. The specimens were securely embedded in a tissue-mimicking agar gel matrix and submerged in degassed phosphate-buffered saline to mimic in vivo environment. The HMI setup consisted of a HIFU transducer confocally aligned with an imaging transducer to induce an oscillatory radiation force and estimate the resulting displacement. 3D HMI displacement maps were reconstructed to represent the relative tissue stiffness in 3D. The average peak-to-peak displacement was found to be significantly different (p = 0.003) between normal breast tissue and invasive ductal carcinoma. There were also significant differences before and after HMIFU ablation in both the normal (53.84 % decrease) and invasive ductal carcinoma (44.69 % decrease) specimens. HMI can be used to map and differentiate relative stiffness in postsurgical normal and pathological breast tissues. HMIFU can also successfully monitor thermal ablations in normal and pathological human breast specimens. This HMI technique may lead to a new clinical tool for breast tumor imaging and HIFU treatment monitoring.

Multi-focus image fusion using a guided-filter-based difference image.

PubMed

Yan, Xiang; Qin, Hanlin; Li, Jia; Zhou, Huixin; Yang, Tingwu

2016-03-20

The aim of multi-focus image fusion technology is to integrate different partially focused images into one all-focused image. To realize this goal, a new multi-focus image fusion method based on a guided filter is proposed and an efficient salient feature extraction method is presented in this paper. Furthermore, feature extraction is primarily the main objective of the present work. Based on salient feature extraction, the guided filter is first used to acquire the smoothing image containing the most sharpness regions. To obtain the initial fusion map, we compose a mixed focus measure by combining the variance of image intensities and the energy of the image gradient together. Then, the initial fusion map is further processed by a morphological filter to obtain a good reprocessed fusion map. Lastly, the final fusion map is determined via the reprocessed fusion map and is optimized by a guided filter. Experimental results demonstrate that the proposed method does markedly improve the fusion performance compared to previous fusion methods and can be competitive with or even outperform state-of-the-art fusion methods in terms of both subjective visual effects and objective quality metrics.

Mobile object retrieval in server-based image databases

NASA Astrophysics Data System (ADS)

Manger, D.; Pagel, F.; Widak, H.

2013-05-01

The increasing number of mobile phones equipped with powerful cameras leads to huge collections of user-generated images. To utilize the information of the images on site, image retrieval systems are becoming more and more popular to search for similar objects in an own image database. As the computational performance and the memory capacity of mobile devices are constantly increasing, this search can often be performed on the device itself. This is feasible, for example, if the images are represented with global image features or if the search is done using EXIF or textual metadata. However, for larger image databases, if multiple users are meant to contribute to a growing image database or if powerful content-based image retrieval methods with local features are required, a server-based image retrieval backend is needed. In this work, we present a content-based image retrieval system with a client server architecture working with local features. On the server side, the scalability to large image databases is addressed with the popular bag-of-word model with state-of-the-art extensions. The client end of the system focuses on a lightweight user interface presenting the most similar images of the database highlighting the visual information which is common with the query image. Additionally, new images can be added to the database making it a powerful and interactive tool for mobile contentbased image retrieval.

Monitoring tumor growth and treatment in small animals with magnetic resonance and optical tomographic imaging

NASA Astrophysics Data System (ADS)

Masciotti, J.; Provenzano, F.; Papa, J.; Klose, A.; Hur, J.; Gu, X.; Yamashiro, D.; Kandel, J.; Hielscher, A. H.

2006-02-01

Small animal models are employed to simulate disease in humans and to study its progression, what factors are important to the disease process, and to study the disease treatment. Biomedical imaging modalities such as magnetic resonance imaging (MRI) and Optical Tomography make it possible to non-invasively monitor the progression of diseases in living small animals and study the efficacy of drugs and treatment protocols. MRI is an established imaging modality capable of obtaining high resolution anatomical images and along with contrast agents allow the studying of blood volume. Optical tomography, on the other hand, is an emerging imaging modality, which, while much lower in spatial resolution, can separate the effects of oxyhemoglobin, deoxyhemoglobin, and blood volume with high temporal resolution. In this study we apply these modalities to imaging the growth of kidney tumors and then there treatment by an anti-VEGF agent. We illustrate how these imaging modalities have their individual uses, but can still supplement each other and cross validation can be performed.

Improving treatment geometries in total skin electron therapy: Experimental investigation of linac angles and floor scatter dose contributions using Cherenkov imaging.

PubMed

Andreozzi, Jacqueline M; Brůža, Petr; Tendler, Irwin I; Mooney, Karen E; Jarvis, Lesley A; Cammin, Jochen; Li, Harold; Pogue, Brian W; Gladstone, David J

2018-06-01

The purpose of this study was to identify the optimal treatment geometry for total skin electron therapy (TSET) using a new optimization metric from Cherenkov image analysis, and to investigate the sensitivity of the Cherenkov imaging method to floor scatter effects in this unique treatment setup. Cherenkov imaging using an intensified charge coupled device (ICCD) was employed to measure the relative surface dose distribution as a 2D image in the total skin electron treatment plane. A 1.2 m × 2.2 m × 1 cm white polyethylene sheet was placed vertically at a source to surface distance (SSD) of 300 cm, and irradiated with 6 MeV high dose rate TSET beams. The linear accelerator coordinate system used stipulates 0° is the bottom of the gantry arc, and progresses counterclockwise so that gantry angle 270° produces a horizontal beam orthogonal to the treatment plane. First, all unique pairs of treatment beams were analyzed to determine the performance of the currently recommended symmetric treatment angles (±20° from the horizontal), compared to treatment geometries unconstrained to upholding gantry angle symmetry. This was performed on two medical linear accelerators (linacs). Second, the extent of the floor scatter contributions to measured surface dose at the extended SSD required for TSET were imaged using three gantry angles of incidence: 270° (horizontal), 253° (-17°), and 240° (-30°). Images of the surface dose profile at each angle were compared to the standard concrete floor when steel plates, polyvinyl chloride (PVC), and solid water were placed on the ground at the base of the treatment plane. Postprocessing of these images allowed for comparison of floor material-based scatter profiles with previously published simulation results. Analysis of the symmetric treatment geometry (270 ± 20°) and the identified optimal treatment geometry (270 + 23° and 270 - 17°) showed a 16% increase in the 90% isodose area for the latter field pair on the first

Peptide-functionalized quantum dots for potential applications in the imaging and treatment of obesity.

PubMed

Thovhogi, Ntevheleni; Sibuyi, Nicole Remaliah Samantha; Onani, Martin Opiyo; Meyer, Mervin; Madiehe, Abram Madimabe

2018-01-01

Obesity is a worldwide epidemic affecting millions of people. The current pharmacological treatment of obesity remains limited and ineffective due to drugs' undesirable side effects. Hence, there is a need for novel or improved strategies for long-term therapies that will help prevent the disease progression into other chronic diseases. Nanotechnology holds the future for the treatment of obesity because of its versatility, as shown by improved drug efficiency and safety in cancer clinical trials. Nano-based drug delivery systems could potentially do the same for obesity through targeted drug delivery. This study investigated the use of peptide-functionalized quantum dots (QDs) for the imaging of prohibitin (PHB)-expressing cells in vitro and in diet-induced obese rats, which could potentially be used as nanocarriers of antiobesity drugs. Cadmium (Cd)-based QDs were functionalized with an adipose homing peptide (AHP) and injected intravenously into lean and obese Wistar rats. Biodistribution of the QDs was analyzed by an IVIS ® Lumina XR imaging system and inductively coupled plasma optical emission spectroscopy (ICP-OES). For in vitro studies, PHB-expressing (Caco-2 and MCF-7) and non-PHB-expressing (KMST-6 and CHO) cells were exposed to either unfunctionalized QDs (QD625) or AHP-functionalized QDs (AHP-QD625) and analyzed by fluorescence microscopy. AHP-QD625 accumulated significantly in PHB-expressing cells in vitro when compared with non-PHB-expressing cells. In vivo data indicated that QD625 accumulated mainly in the reticuloendothelial system (RES) organs, while the AHP-QD625 accumulated mostly in the white adipose tissues (WATs). AHP-functionalized QDs were successfully and selectively delivered to the PHB-expressing cells in vitro (Caco-2 and MCF-7 cells) and in the WAT vasculature in vivo. This nanotechnology-based approach could potentially be used for dual targeted drug delivery and molecular imaging of adipose tissues in obese patients in real time.

Image2000: A Free, Innovative, Java Based Imaging Package

NASA Technical Reports Server (NTRS)

Pell, Nicholas; Wheeler, Phil; Cornwell, Carl; Matusow, David; Obenschain, Arthur F. (Technical Monitor)

2001-01-01

The National Aeronautics and Space Administration (NASA) Goddard Space Flight Center's (GSFC) Scientific and Educational Endeavors (SEE) and the Center for Image Processing in Education (CIPE) use satellite image processing as part of their science lessons developed for students and educators. The image processing products that they use, as part of these lessons, no longer fulfill the needs of SEE and CIPE because these products are either dependent on a particular computing platform, hard to customize and extend, or do not have enough functionality. SEE and CIPE began looking for what they considered the "perfect" image processing tool that was platform independent, rich in functionality and could easily be extended and customized for their purposes. At the request of SEE, NASA's GSFC, code 588 the Advanced Architectures and Automation Branch developed a powerful new Java based image processing endeavors.

Neural-net-based image matching

NASA Astrophysics Data System (ADS)

Jerebko, Anna K.; Barabanov, Nikita E.; Luciv, Vadim R.; Allinson, Nigel M.

2000-04-01

The paper describes a neural-based method for matching spatially distorted image sets. The matching of partially overlapping images is important in many applications-- integrating information from images formed from different spectral ranges, detecting changes in a scene and identifying objects of differing orientations and sizes. Our approach consists of extracting contour features from both images, describing the contour curves as sets of line segments, comparing these sets, determining the corresponding curves and their common reference points, calculating the image-to-image co-ordinate transformation parameters on the basis of the most successful variant of the derived curve relationships. The main steps are performed by custom neural networks. The algorithms describe in this paper have been successfully tested on a large set of images of the same terrain taken in different spectral ranges, at different seasons and rotated by various angles. In general, this experimental verification indicates that the proposed method for image fusion allows the robust detection of similar objects in noisy, distorted scenes where traditional approaches often fail.

Patient specific optimization-based treatment planning for catheter-based ultrasound hyperthermia and thermal ablation

NASA Astrophysics Data System (ADS)

Prakash, Punit; Chen, Xin; Wootton, Jeffery; Pouliot, Jean; Hsu, I.-Chow; Diederich, Chris J.

2009-02-01

A 3D optimization-based thermal treatment planning platform has been developed for the application of catheter-based ultrasound hyperthermia in conjunction with high dose rate (HDR) brachytherapy for treating advanced pelvic tumors. Optimal selection of applied power levels to each independently controlled transducer segment can be used to conform and maximize therapeutic heating and thermal dose coverage to the target region, providing significant advantages over current hyperthermia technology and improving treatment response. Critical anatomic structures, clinical target outlines, and implant/applicator geometries were acquired from sequential multi-slice 2D images obtained from HDR treatment planning and used to reconstruct patient specific 3D biothermal models. A constrained optimization algorithm was devised and integrated within a finite element thermal solver to determine a priori the optimal applied power levels and the resulting 3D temperature distributions such that therapeutic heating is maximized within the target, while placing constraints on maximum tissue temperature and thermal exposure of surrounding non-targeted tissue. This optimizationbased treatment planning and modeling system was applied on representative cases of clinical implants for HDR treatment of cervix and prostate to evaluate the utility of this planning approach. The planning provided significant improvement in achievable temperature distributions for all cases, with substantial increase in T90 and thermal dose (CEM43T90) coverage to the hyperthermia target volume while decreasing maximum treatment temperature and reducing thermal dose exposure to surrounding non-targeted tissues and thermally sensitive rectum and bladder. This optimization based treatment planning platform with catheter-based ultrasound applicators is a useful tool that has potential to significantly improve the delivery of hyperthermia in conjunction with HDR brachytherapy. The planning platform has been extended

Using PACS and wavelet-based image compression in a wide-area network to support radiation therapy imaging applications for satellite hospitals

NASA Astrophysics Data System (ADS)

Smith, Charles L.; Chu, Wei-Kom; Wobig, Randy; Chao, Hong-Yang; Enke, Charles

1999-07-01

An ongoing PACS project at our facility has been expanded to include providing and managing images used for routine clinical operation of the department of radiation oncology. The intent of our investigation has been to enable out clinical radiotherapy service to enter the tele-medicine environment through the use of a PACS system initially implemented in the department of radiology. The backbone for the imaging network includes five CT and three MR scanners located across three imaging centers. A PC workstation in the department of radiation oncology was used to transmit CT imags to a satellite facility located approximately 60 miles from the primary center. Chest CT images were used to analyze network transmission performance. Connectivity established between the primary department and satellite has fulfilled all image criteria required by the oncologist. Establishing the link tot eh oncologist at the satellite diminished bottlenecking of imaging related tasks at the primary facility due to physician absence. A 30:1 compression ratio using a wavelet-based algorithm provided clinically acceptable images treatment planning. Clinical radiotherapy images can be effectively managed in a wide- area-network to link satellite facilities to larger clinical centers.

On combining image-based and ontological semantic dissimilarities for medical image retrieval applications

PubMed Central

Kurtz, Camille; Depeursinge, Adrien; Napel, Sandy; Beaulieu, Christopher F.; Rubin, Daniel L.

2014-01-01

Computer-assisted image retrieval applications can assist radiologists by identifying similar images in archives as a means to providing decision support. In the classical case, images are described using low-level features extracted from their contents, and an appropriate distance is used to find the best matches in the feature space. However, using low-level image features to fully capture the visual appearance of diseases is challenging and the semantic gap between these features and the high-level visual concepts in radiology may impair the system performance. To deal with this issue, the use of semantic terms to provide high-level descriptions of radiological image contents has recently been advocated. Nevertheless, most of the existing semantic image retrieval strategies are limited by two factors: they require manual annotation of the images using semantic terms and they ignore the intrinsic visual and semantic relationships between these annotations during the comparison of the images. Based on these considerations, we propose an image retrieval framework based on semantic features that relies on two main strategies: (1) automatic “soft” prediction of ontological terms that describe the image contents from multi-scale Riesz wavelets and (2) retrieval of similar images by evaluating the similarity between their annotations using a new term dissimilarity measure, which takes into account both image-based and ontological term relations. The combination of these strategies provides a means of accurately retrieving similar images in databases based on image annotations and can be considered as a potential solution to the semantic gap problem. We validated this approach in the context of the retrieval of liver lesions from computed tomographic (CT) images and annotated with semantic terms of the RadLex ontology. The relevance of the retrieval results was assessed using two protocols: evaluation relative to a dissimilarity reference standard defined for pairs

Image dehazing based on non-local saturation

NASA Astrophysics Data System (ADS)

Wang, Linlin; Zhang, Qian; Yang, Deyun; Hou, Yingkun; He, Xiaoting

2018-04-01

In this paper, a method based on non-local saturation algorithm is proposed to avoid block and halo effect for single image dehazing with dark channel prior. First we convert original image from RGB color space into HSV color space with the idea of non-local method. Image saturation is weighted equally by the size of fixed window according to image resolution. Second we utilize the saturation to estimate the atmospheric light value and transmission rate. Then through the function of saturation and transmission, the haze-free image is obtained based on the atmospheric scattering model. Comparing the results of existing methods, our method can restore image color and enhance contrast. We guarantee the proposed method with quantitative and qualitative evaluation respectively. Experiments show the better visual effect with high efficiency.

An image mosaic method based on corner

NASA Astrophysics Data System (ADS)

Jiang, Zetao; Nie, Heting

2015-08-01

In view of the shortcomings of the traditional image mosaic, this paper describes a new algorithm for image mosaic based on the Harris corner. Firstly, Harris operator combining the constructed low-pass smoothing filter based on splines function and circular window search is applied to detect the image corner, which allows us to have better localisation performance and effectively avoid the phenomenon of cluster. Secondly, the correlation feature registration is used to find registration pair, remove the false registration using random sampling consensus. Finally use the method of weighted trigonometric combined with interpolation function for image fusion. The experiments show that this method can effectively remove the splicing ghosting and improve the accuracy of image mosaic.

Feature-based Alignment of Volumetric Multi-modal Images

PubMed Central

Toews, Matthew; Zöllei, Lilla; Wells, William M.

2014-01-01

This paper proposes a method for aligning image volumes acquired from different imaging modalities (e.g. MR, CT) based on 3D scale-invariant image features. A novel method for encoding invariant feature geometry and appearance is developed, based on the assumption of locally linear intensity relationships, providing a solution to poor repeatability of feature detection in different image modalities. The encoding method is incorporated into a probabilistic feature-based model for multi-modal image alignment. The model parameters are estimated via a group-wise alignment algorithm, that iteratively alternates between estimating a feature-based model from feature data, then realigning feature data to the model, converging to a stable alignment solution with few pre-processing or pre-alignment requirements. The resulting model can be used to align multi-modal image data with the benefits of invariant feature correspondence: globally optimal solutions, high efficiency and low memory usage. The method is tested on the difficult RIRE data set of CT, T1, T2, PD and MP-RAGE brain images of subjects exhibiting significant inter-subject variability due to pathology. PMID:24683955

An effective content-based image retrieval technique for image visuals representation based on the bag-of-visual-words model

PubMed Central

Jabeen, Safia; Mehmood, Zahid; Mahmood, Toqeer; Saba, Tanzila; Rehman, Amjad; Mahmood, Muhammad Tariq

2018-01-01

For the last three decades, content-based image retrieval (CBIR) has been an active research area, representing a viable solution for retrieving similar images from an image repository. In this article, we propose a novel CBIR technique based on the visual words fusion of speeded-up robust features (SURF) and fast retina keypoint (FREAK) feature descriptors. SURF is a sparse descriptor whereas FREAK is a dense descriptor. Moreover, SURF is a scale and rotation-invariant descriptor that performs better in the case of repeatability, distinctiveness, and robustness. It is robust to noise, detection errors, geometric, and photometric deformations. It also performs better at low illumination within an image as compared to the FREAK descriptor. In contrast, FREAK is a retina-inspired speedy descriptor that performs better for classification-based problems as compared to the SURF descriptor. Experimental results show that the proposed technique based on the visual words fusion of SURF-FREAK descriptors combines the features of both descriptors and resolves the aforementioned issues. The qualitative and quantitative analysis performed on three image collections, namely Corel-1000, Corel-1500, and Caltech-256, shows that proposed technique based on visual words fusion significantly improved the performance of the CBIR as compared to the feature fusion of both descriptors and state-of-the-art image retrieval techniques. PMID:29694429

Biometric image enhancement using decision rule based image fusion techniques

NASA Astrophysics Data System (ADS)

Sagayee, G. Mary Amirtha; Arumugam, S.

2010-02-01

Introducing biometrics into information systems may result in considerable benefits. Most of the researchers confirmed that the finger print is widely used than the iris or face and more over it is the primary choice for most privacy concerned applications. For finger prints applications, choosing proper sensor is at risk. The proposed work deals about, how the image quality can be improved by introducing image fusion technique at sensor levels. The results of the images after introducing the decision rule based image fusion technique are evaluated and analyzed with its entropy levels and root mean square error.

Planning Image-Based Measurements in Wind Tunnels by Virtual Imaging

NASA Technical Reports Server (NTRS)

Kushner, Laura Kathryn; Schairer, Edward T.

2011-01-01

Virtual imaging is routinely used at NASA Ames Research Center to plan the placement of cameras and light sources for image-based measurements in production wind tunnel tests. Virtual imaging allows users to quickly and comprehensively model a given test situation, well before the test occurs, in order to verify that all optical testing requirements will be met. It allows optimization of the placement of cameras and light sources and leads to faster set-up times, thereby decreasing tunnel occupancy costs. This paper describes how virtual imaging was used to plan optical measurements for three tests in production wind tunnels at NASA Ames.

Recent advances in oral oncology 2008; squamous cell carcinoma imaging, treatment, prognostication and treatment outcomes.

PubMed

Scully, Crispian; Bagan, Jose V

2009-06-01

This paper provides a synopsis of the main papers on diagnosis, imaging, treatment, prognostication and treatment outcomes in patients with oral and oropharyngeal squamous cell carcinoma (OSCC) and head and neck SCC (HNSCC) published in 2008 in Oral Oncology - an international interdisciplinary journal which publishes high quality original research, clinical trials and review articles, and all other scientific articles relating to the aetiopathogenesis, epidemiology, prevention, clinical features, diagnosis, treatment and management of patients with neoplasms in the head and neck, and orofacial disease in patients with malignant disease.

Computer-Based Image Analysis for Plus Disease Diagnosis in Retinopathy of Prematurity

PubMed Central

Wittenberg, Leah A.; Jonsson, Nina J.; Chan, RV Paul; Chiang, Michael F.

2014-01-01

Presence of plus disease in retinopathy of prematurity (ROP) is an important criterion for identifying treatment-requiring ROP. Plus disease is defined by a standard published photograph selected over 20 years ago by expert consensus. However, diagnosis of plus disease has been shown to be subjective and qualitative. Computer-based image analysis, using quantitative methods, has potential to improve the objectivity of plus disease diagnosis. The objective was to review the published literature involving computer-based image analysis for ROP diagnosis. The PubMed and Cochrane library databases were searched for the keywords “retinopathy of prematurity” AND “image analysis” AND/OR “plus disease.” Reference lists of retrieved articles were searched to identify additional relevant studies. All relevant English-language studies were reviewed. There are four main computer-based systems, ROPtool (AU ROC curve, plus tortuosity 0.95, plus dilation 0.87), RISA (AU ROC curve, arteriolar TI 0.71, venular diameter 0.82), Vessel Map (AU ROC curve, arteriolar dilation 0.75, venular dilation 0.96), and CAIAR (AU ROC curve, arteriole tortuosity 0.92, venular dilation 0.91), attempting to objectively analyze vessel tortuosity and dilation in plus disease in ROP. Some of them show promise for identification of plus disease using quantitative methods. This has potential to improve the diagnosis of plus disease, and may contribute to the management of ROP using both traditional binocular indirect ophthalmoscopy and image-based telemedicine approaches. PMID:21366159

Different source image fusion based on FPGA

NASA Astrophysics Data System (ADS)

Luo, Xiao; Piao, Yan

2016-03-01

The fusion technology of video image is to make the video obtained by different image sensors complementary to each other by some technical means, so as to obtain the video information which is rich in information and suitable for the human eye system. Infrared cameras in harsh environments such as when smoke, fog and low light situations penetrating power, but the ability to obtain the details of the image is poor, does not meet the human visual system. Single visible light imaging can be rich in detail, high resolution images and for the visual system, but the visible image easily affected by the external environment. Infrared image and visible image fusion process involved in the video image fusion algorithm complexity and high calculation capacity, have occupied more memory resources, high clock rate requirements, such as software, c ++, c, etc. to achieve more, but based on Hardware platform less. In this paper, based on the imaging characteristics of infrared images and visible light images, the software and hardware are combined to obtain the registration parameters through software matlab, and the gray level weighted average method is used to implement the hardware platform. Information fusion, and finally the fusion image can achieve the goal of effectively improving the acquisition of information to increase the amount of information in the image.

A digital image-based method for determining of total acidity in red wines using acid-base titration without indicator.

PubMed

Tôrres, Adamastor Rodrigues; Lyra, Wellington da Silva; de Andrade, Stéfani Iury Evangelista; Andrade, Renato Allan Navarro; da Silva, Edvan Cirino; Araújo, Mário César Ugulino; Gaião, Edvaldo da Nóbrega

2011-05-15

This work proposes the use of digital image-based method for determination of total acidity in red wines by means of acid-base titration without using an external indicator or any pre-treatment of the sample. Digital images present the colour of the emergent radiation which is complementary to the radiation absorbed by anthocyanines present in wines. Anthocyanines change colour depending on the pH of the medium, and from the variation of colour in the images obtained during titration, the end point can be localized with accuracy and precision. RGB-based values were employed to build titration curves, and end points were localized by second derivative curves. The official method recommends potentiometric titration with a NaOH standard solution, and sample dilution until the pH reaches 8.2-8.4. In order to illustrate the feasibility of the proposed method, titrations of ten red wines were carried out. Results were compared with the reference method, and no statistically significant difference was observed between the results by applying the paired t-test at the 95% confidence level. The proposed method yielded more precise results than the official method. This is due to the trivariate nature of the measurements (RGB), associated with digital images. Copyright © 2011 Elsevier B.V. All rights reserved.

Research on the lesion segmentation of breast tumor MR images based on FCM-DS theory

NASA Astrophysics Data System (ADS)

Zhang, Liangbin; Ma, Wenjun; Shen, Xing; Li, Yuehua; Zhu, Yuemin; Chen, Li; Zhang, Su

2017-03-01

Magnetic resonance imaging (MRI) plays an important role in the treatment of breast tumor by high intensity focused ultrasound (HIFU). The doctors evaluate the scale, distribution and the statement of benign or malignancy of breast tumor by analyzing variety modalities of MRI, such as the T2, DWI and DCE images for making accurate preoperative treatment plan and evaluating the effect of the operation. This paper presents a method of lesion segmentation of breast tumor based on FCM-DS theory. Fuzzy c-means clustering (FCM) algorithm combined with Dempster-Shafer (DS) theory is used to process the uncertainty of information, segmenting the lesion areas on DWI and DCE modalities of MRI and reducing the scale of the uncertain parts. Experiment results show that FCM-DS can fuse the DWI and DCE images to achieve accurate segmentation and display the statement of benign or malignancy of lesion area by Time-Intensity Curve (TIC), which could be beneficial in making preoperative treatment plan and evaluating the effect of the therapy.

Developing students’ ideas about lens imaging: teaching experiments with an image-based approach

NASA Astrophysics Data System (ADS)

Grusche, Sascha

2017-07-01

Lens imaging is a classic topic in physics education. To guide students from their holistic viewpoint to the scientists’ analytic viewpoint, an image-based approach to lens imaging has recently been proposed. To study the effect of the image-based approach on undergraduate students’ ideas, teaching experiments are performed and evaluated using qualitative content analysis. Some of the students’ ideas have not been reported before, namely those related to blurry lens images, and those developed by the proposed teaching approach. To describe learning pathways systematically, a conception-versus-time coordinate system is introduced, specifying how teaching actions help students advance toward a scientific understanding.

Image denoising based on noise detection

NASA Astrophysics Data System (ADS)

Jiang, Yuanxiang; Yuan, Rui; Sun, Yuqiu; Tian, Jinwen

2018-03-01

Because of the noise points in the images, any operation of denoising would change the original information of non-noise pixel. A noise detection algorithm based on fractional calculus was proposed to denoise in this paper. Convolution of the image was made to gain direction gradient masks firstly. Then, the mean gray was calculated to obtain the gradient detection maps. Logical product was made to acquire noise position image next. Comparisons in the visual effect and evaluation parameters after processing, the results of experiment showed that the denoising algorithms based on noise were better than that of traditional methods in both subjective and objective aspects.

Image-based corrosion recognition for ship steel structures

NASA Astrophysics Data System (ADS)

Ma, Yucong; Yang, Yang; Yao, Yuan; Li, Shengyuan; Zhao, Xuefeng

2018-03-01

Ship structures are subjected to corrosion inevitably in service. Existed image-based methods are influenced by the noises in images because they recognize corrosion by extracting features. In this paper, a novel method of image-based corrosion recognition for ship steel structures is proposed. The method utilizes convolutional neural networks (CNN) and will not be affected by noises in images. A CNN used to recognize corrosion was designed through fine-turning an existing CNN architecture and trained by datasets built using lots of images. Combining the trained CNN classifier with a sliding window technique, the corrosion zone in an image can be recognized.

Optical colour image watermarking based on phase-truncated linear canonical transform and image decomposition

NASA Astrophysics Data System (ADS)

Su, Yonggang; Tang, Chen; Li, Biyuan; Lei, Zhenkun

2018-05-01

This paper presents a novel optical colour image watermarking scheme based on phase-truncated linear canonical transform (PT-LCT) and image decomposition (ID). In this proposed scheme, a PT-LCT-based asymmetric cryptography is designed to encode the colour watermark into a noise-like pattern, and an ID-based multilevel embedding method is constructed to embed the encoded colour watermark into a colour host image. The PT-LCT-based asymmetric cryptography, which can be optically implemented by double random phase encoding with a quadratic phase system, can provide a higher security to resist various common cryptographic attacks. And the ID-based multilevel embedding method, which can be digitally implemented by a computer, can make the information of the colour watermark disperse better in the colour host image. The proposed colour image watermarking scheme possesses high security and can achieve a higher robustness while preserving the watermark’s invisibility. The good performance of the proposed scheme has been demonstrated by extensive experiments and comparison with other relevant schemes.

New mobile methods for dietary assessment: review of image-assisted and image-based dietary assessment methods.

PubMed

Boushey, C J; Spoden, M; Zhu, F M; Delp, E J; Kerr, D A

2017-08-01

For nutrition practitioners and researchers, assessing dietary intake of children and adults with a high level of accuracy continues to be a challenge. Developments in mobile technologies have created a role for images in the assessment of dietary intake. The objective of this review was to examine peer-reviewed published papers covering development, evaluation and/or validation of image-assisted or image-based dietary assessment methods from December 2013 to January 2016. Images taken with handheld devices or wearable cameras have been used to assist traditional dietary assessment methods for portion size estimations made by dietitians (image-assisted methods). Image-assisted approaches can supplement either dietary records or 24-h dietary recalls. In recent years, image-based approaches integrating application technology for mobile devices have been developed (image-based methods). Image-based approaches aim at capturing all eating occasions by images as the primary record of dietary intake, and therefore follow the methodology of food records. The present paper reviews several image-assisted and image-based methods, their benefits and challenges; followed by details on an image-based mobile food record. Mobile technology offers a wide range of feasible options for dietary assessment, which are easier to incorporate into daily routines. The presented studies illustrate that image-assisted methods can improve the accuracy of conventional dietary assessment methods by adding eating occasion detail via pictures captured by an individual (dynamic images). All of the studies reduced underreporting with the help of images compared with results with traditional assessment methods. Studies with larger sample sizes are needed to better delineate attributes with regards to age of user, degree of error and cost.

SU-E-J-153: Reconstructing 4D Cone Beam CT Images for Clinical QA of Lung SABR Treatments

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

Beaudry, J; Bergman, A; British Columbia Cancer Agency, Vancouver, BC

Purpose: To verify that the planned Primary Target Volume (PTV) and Internal Gross Tumor Volume (IGTV) fully enclose a moving lung tumor volume as visualized on a pre-SABR treatment verification 4D Cone Beam CT. Methods: Daily 3DCBCT image sets were acquired immediately prior to treatment for 10 SABR lung patients using the on-board imaging system integrated into a Varian TrueBeam (v1.6: no 4DCBCT module available). Respiratory information was acquired during the scan using the Varian RPM system. The CBCT projections were sorted into 8 bins offline, both by breathing phase and amplitude, using in-house software. An iterative algorithm based onmore » total variation minimization, implemented in the open source reconstruction toolkit (RTK), was used to reconstruct the binned projections into 4DCBCT images. The relative tumor motion was quantified by tracking the centroid of the tumor volume from each 4DCBCT image. Following CT-CBCT registration, the planning CT volumes were compared to the location of the CBCT tumor volume as it moves along its breathing trajectory. An overlap metric quantified the ability of the planned PTV and IGTV to contain the tumor volume at treatment. Results: The 4DCBCT reconstructed images visibly show the tumor motion. The mean overlap between the planned PTV (IGTV) and the 4DCBCT tumor volumes was 100% (94%), with an uncertainty of 5% from the 4DCBCT tumor volume contours. Examination of the tumor motion and overlap metric verify that the IGTV drawn at the planning stage is a good representation of the tumor location at treatment. Conclusion: It is difficult to compare GTV volumes from a 4DCBCT and a planning CT due to image quality differences. However, it was possible to conclude the GTV remained within the PTV 100% of the time thus giving the treatment staff confidence that SABR lung treatements are being delivered accurately.« less

Binary-space-partitioned images for resolving image-based visibility.

PubMed

Fu, Chi-Wing; Wong, Tien-Tsin; Tong, Wai-Shun; Tang, Chi-Keung; Hanson, Andrew J

2004-01-01

We propose a novel 2D representation for 3D visibility sorting, the Binary-Space-Partitioned Image (BSPI), to accelerate real-time image-based rendering. BSPI is an efficient 2D realization of a 3D BSP tree, which is commonly used in computer graphics for time-critical visibility sorting. Since the overall structure of a BSP tree is encoded in a BSPI, traversing a BSPI is comparable to traversing the corresponding BSP tree. BSPI performs visibility sorting efficiently and accurately in the 2D image space by warping the reference image triangle-by-triangle instead of pixel-by-pixel. Multiple BSPIs can be combined to solve "disocclusion," when an occluded portion of the scene becomes visible at a novel viewpoint. Our method is highly automatic, including a tensor voting preprocessing step that generates candidate image partition lines for BSPIs, filters the noisy input data by rejecting outliers, and interpolates missing information. Our system has been applied to a variety of real data, including stereo, motion, and range images.

Core needle biopsy guidance based on EMOCT imaging (Conference Presentation)

NASA Astrophysics Data System (ADS)

Iftimia, Nicusor V.; Park, Jesung; Maguluri, Gopi

2016-03-01

We present a novel method, based on encoder mapping OCT imaging, for real-time guidance of core biopsy procedures. This method provides real-time feedback to the interventional radiologist, such that he/she can reorient the needle during the biopsy and sample the most representative area of the suspicious mass that is being investigated. This aspect is very important for tailoring therapy to the specific cancer based on biomarker analysis, which will become one of the next big advances in our search for the optimal cancer therapy. To enable individualized treatment, the genetic constitution and the DNA repair status in the affected areas is needed for each patient. Thus, representative sampling of the tumor is needed for analyzing various biomarkers, which are used as a tool to personalize cancer therapy. The encoder-based OCT enables samping of large size masses and provides full control on the imaging probe, which is passed through the bore of the biopsy guidance needle. The OCT image is built gradually, based on the feedback of an optical encoder which senses the incremental movement of the needle with a few microns resolution. Tissue mapping is independent of the needle speed, while it is advanced through the tissue. The OCT frame is analyzed in real-time and tissue cellularity is reported in a very simple manner (pie chart). Our preliminary study on a rabbit model of cancer has demonstrated the capability of this technology for accurately differentiating between viable cancer and heterogeneous or necrotic tissue.

Juvenile Dermatomyositis: Key Roles of Muscle Magnetic Resonance Imaging and Early Aggressive Treatment.

PubMed

Corral-Magaña, O; Bauzá-Alonso, A F; Escudero-Góngora, M M; Lacruz, L; Martín-Santiago, A

2017-09-12

Juvenile dermatomyositis is a rare systemic connective tissue disease with onset during childhood. It presents clinically with proximal muscle weakness and characteristic skin involvement. Diagnosis is based on the Bohan and Peter criteria, though many authors are now substituting biopsy with muscle magnetic resonance imaging (MRI) for both diagnosis and follow-up. Without intensive early treatment, complications such as calcinosis cutis and lipodystrophy can develop in the chronic phases of the disease. Early recognition is therefore key to management. We present a series of 5 patients who were diagnosed with Juvenile dermatomyositis on muscle MRI without undergoing muscle biopsy and who received early treatment. We draw attention to the usefulness of muscle MRI for the diagnosis of muscle involvement and to the importance of early initiation of intensive treatment to prevent complications. Copyright © 2017 AEDV. Publicado por Elsevier España, S.L.U. All rights reserved.

High dynamic range image acquisition based on multiplex cameras

NASA Astrophysics Data System (ADS)

Zeng, Hairui; Sun, Huayan; Zhang, Tinghua

2018-03-01

High dynamic image is an important technology of photoelectric information acquisition, providing higher dynamic range and more image details, and it can better reflect the real environment, light and color information. Currently, the method of high dynamic range image synthesis based on different exposure image sequences cannot adapt to the dynamic scene. It fails to overcome the effects of moving targets, resulting in the phenomenon of ghost. Therefore, a new high dynamic range image acquisition method based on multiplex cameras system was proposed. Firstly, different exposure images sequences were captured with the camera array, using the method of derivative optical flow based on color gradient to get the deviation between images, and aligned the images. Then, the high dynamic range image fusion weighting function was established by combination of inverse camera response function and deviation between images, and was applied to generated a high dynamic range image. The experiments show that the proposed method can effectively obtain high dynamic images in dynamic scene, and achieves good results.

Analyser-based mammography using single-image reconstruction.

PubMed

Briedis, Dahliyani; Siu, Karen K W; Paganin, David M; Pavlov, Konstantin M; Lewis, Rob A

2005-08-07

We implement an algorithm that is able to decode a single analyser-based x-ray phase-contrast image of a sample, converting it into an equivalent conventional absorption-contrast radiograph. The algorithm assumes the projection approximation for x-ray propagation in a single-material object embedded in a substrate of approximately uniform thickness. Unlike the phase-contrast images, which have both directional bias and a bias towards edges present in the sample, the reconstructed images are directly interpretable in terms of the projected absorption coefficient of the sample. The technique was applied to a Leeds TOR[MAM] phantom, which is designed to test mammogram quality by the inclusion of simulated microcalcifications, filaments and circular discs. This phantom was imaged at varying doses using three modalities: analyser-based synchrotron phase-contrast images converted to equivalent absorption radiographs using our algorithm, slot-scanned synchrotron imaging and imaging using a conventional mammography unit. Features in the resulting images were then assigned a quality score by volunteers. The single-image reconstruction method achieved higher scores at equivalent and lower doses than the conventional mammography images, but no improvement of visualization of the simulated microcalcifications, and some degradation in image quality at reduced doses for filament features.

Mechanism and non-mechanism based imaging biomarkers for assessing biological response to treatment in non-small cell lung cancer.

PubMed

Weller, A; O'Brien, M E R; Ahmed, M; Popat, S; Bhosle, J; McDonald, F; Yap, T A; Du, Y; Vlahos, I; deSouza, N M

2016-05-01

Therapeutic options in locally advanced non-small cell lung cancer (NSCLC) have expanded in the past decade to include a palate of targeted interventions such as high dose targeted thermal ablations, radiotherapy and growing platform of antibody and small molecule therapies and immunotherapies. Although these therapies have varied mechanisms of action, they often induce changes in tumour architecture and microenvironment such that response is not always accompanied by early reduction in tumour mass, and evaluation by criteria other than size is needed to report more effectively on response. Functional imaging techniques, which probe the tumour and its microenvironment through novel positron emission tomography and magnetic resonance imaging techniques, offer more detailed insights into and quantitation of tumour response than is available on anatomical imaging alone. Use of these biomarkers, or other rational combinations as readouts of pathological response in NSCLC have potential to provide more accurate predictors of treatment outcomes. In this article, the robustness of the more commonly available positron emission tomography and magnetic resonance imaging biomarker indices is examined and the evidence for their application in NSCLC is reviewed. Copyright © 2016 Elsevier Ltd. All rights reserved.

Supervoxels for graph cuts-based deformable image registration using guided image filtering

NASA Astrophysics Data System (ADS)

Szmul, Adam; Papież, Bartłomiej W.; Hallack, Andre; Grau, Vicente; Schnabel, Julia A.

2017-11-01

We propose combining a supervoxel-based image representation with the concept of graph cuts as an efficient optimization technique for three-dimensional (3-D) deformable image registration. Due to the pixels/voxels-wise graph construction, the use of graph cuts in this context has been mainly limited to two-dimensional (2-D) applications. However, our work overcomes some of the previous limitations by posing the problem on a graph created by adjacent supervoxels, where the number of nodes in the graph is reduced from the number of voxels to the number of supervoxels. We demonstrate how a supervoxel image representation combined with graph cuts-based optimization can be applied to 3-D data. We further show that the application of a relaxed graph representation of the image, followed by guided image filtering over the estimated deformation field, allows us to model "sliding motion." Applying this method to lung image registration results in highly accurate image registration and anatomically plausible estimations of the deformations. Evaluation of our method on a publicly available computed tomography lung image dataset leads to the observation that our approach compares very favorably with state of the art methods in continuous and discrete image registration, achieving target registration error of 1.16 mm on average per landmark.

On-demand server-side image processing for web-based DICOM image display

NASA Astrophysics Data System (ADS)

Sakusabe, Takaya; Kimura, Michio; Onogi, Yuzo

2000-04-01

Low cost image delivery is needed in modern networked hospitals. If a hospital has hundreds of clients, cost of client systems is a big problem. Naturally, a Web-based system is the most effective solution. But a Web browser could not display medical images with certain image processing such as a lookup table transformation. We developed a Web-based medical image display system using Web browser and on-demand server-side image processing. All images displayed on a Web page are generated from DICOM files on a server, delivered on-demand. User interaction on the Web page is handled by a client-side scripting technology such as JavaScript. This combination makes a look-and-feel of an imaging workstation not only for its functionality but also for its speed. Real time update of images with tracing mouse motion is achieved on Web browser without any client-side image processing which may be done by client-side plug-in technology such as Java Applets or ActiveX. We tested performance of the system in three cases. Single client, small number of clients in a fast speed network, and large number of clients in a normal speed network. The result shows that there are very slight overhead for communication and very scalable in number of clients.

Supervoxels for Graph Cuts-Based Deformable Image Registration Using Guided Image Filtering.

PubMed

Szmul, Adam; Papież, Bartłomiej W; Hallack, Andre; Grau, Vicente; Schnabel, Julia A

2017-10-04

In this work we propose to combine a supervoxel-based image representation with the concept of graph cuts as an efficient optimization technique for 3D deformable image registration. Due to the pixels/voxels-wise graph construction, the use of graph cuts in this context has been mainly limited to 2D applications. However, our work overcomes some of the previous limitations by posing the problem on a graph created by adjacent supervoxels, where the number of nodes in the graph is reduced from the number of voxels to the number of supervoxels. We demonstrate how a supervoxel image representation, combined with graph cuts-based optimization can be applied to 3D data. We further show that the application of a relaxed graph representation of the image, followed by guided image filtering over the estimated deformation field, allows us to model 'sliding motion'. Applying this method to lung image registration, results in highly accurate image registration and anatomically plausible estimations of the deformations. Evaluation of our method on a publicly available Computed Tomography lung image dataset (www.dir-lab.com) leads to the observation that our new approach compares very favorably with state-of-the-art in continuous and discrete image registration methods achieving Target Registration Error of 1.16mm on average per landmark.

Functional brain imaging: an evidence-based analysis.

PubMed

2006-01-01

The objective of this analysis is to review a spectrum of functional brain imaging technologies to identify whether there are any imaging modalities that are more effective than others for various brain pathology conditions. This evidence-based analysis reviews magnetoencephalography (MEG), magnetic resonance spectroscopy (MRS), positron emission tomography (PET), and functional magnetic resonance imaging (fMRI) for the diagnosis or surgical management of the following conditions: Alzheimer's disease (AD), brain tumours, epilepsy, multiple sclerosis (MS), and Parkinson's disease (PD). TARGET POPULATION AND CONDITION Alzheimer's disease is a progressive, degenerative, neurologic condition characterized by cognitive impairment and memory loss. The Canadian Study on Health and Aging estimated that there will be 97,000 incident cases (about 60,000 women) of dementia (including AD) in Canada in 2006. In Ontario, there will be an estimated 950 new cases and 580 deaths due to brain cancer in 2006. Treatments for brain tumours include surgery and radiation therapy. However, one of the limitations of radiation therapy is that it damages tissue though necrosis and scarring. Computed tomography (CT) and magnetic resonance imaging (MRI) may not distinguish between radiation effects and resistant tissue, creating a potential role for functional brain imaging. Epilepsy is a chronic disorder that provokes repetitive seizures. In Ontario, the rate of epilepsy is estimated to be 5 cases per 1,000 people. Most people with epilepsy are effectively managed with drug therapy; but about 50% do not respond to drug therapy. Surgical resection of the seizure foci may be considered in these patients, and functional brain imaging may play a role in localizing the seizure foci. Multiple sclerosis is a progressive, inflammatory, demyelinating disease of the central nervous system (CNS). The cause of MS is unknown; however, it is thought to be due to a combination of etiologies, including

Ground-based full-sky imaging polarimeter based on liquid crystal variable retarders.

PubMed

Zhang, Ying; Zhao, Huijie; Song, Ping; Shi, Shaoguang; Xu, Wujian; Liang, Xiao

2014-04-07

A ground-based full-sky imaging polarimeter based on liquid crystal variable retarders (LCVRs) is proposed in this paper. Our proposed method can be used to realize the rapid detection of the skylight polarization information with hemisphere field-of-view for the visual band. The characteristics of the incidence angle of light on the LCVR are investigated, based on the electrically controlled birefringence. Then, the imaging polarimeter with hemisphere field-of-view is designed. Furthermore, the polarization calibration method with the field-of-view multiplexing and piecewise linear fitting is proposed, based on the rotation symmetry of the polarimeter. The polarization calibration of the polarimeter is implemented with the hemisphere field-of-view. This imaging polarimeter is investigated by the experiment of detecting the skylight image. The consistency between the obtained experimental distribution of polarization angle with that due to Rayleigh scattering model is 90%, which confirms the effectivity of our proposed imaging polarimeter.

First Steps Toward Ultrasound-Based Motion Compensation for Imaging and Therapy: Calibration with an Optical System and 4D PET Imaging

PubMed Central

Schwaab, Julia; Kurz, Christopher; Sarti, Cristina; Bongers, André; Schoenahl, Frédéric; Bert, Christoph; Debus, Jürgen; Parodi, Katia; Jenne, Jürgen Walter

2015-01-01

Target motion, particularly in the abdomen, due to respiration or patient movement is still a challenge in many diagnostic and therapeutic processes. Hence, methods to detect and compensate this motion are required. Diagnostic ultrasound (US) represents a non-invasive and dose-free alternative to fluoroscopy, providing more information about internal target motion than respiration belt or optical tracking. The goal of this project is to develop an US-based motion tracking for real-time motion correction in radiation therapy and diagnostic imaging, notably in 4D positron emission tomography (PET). In this work, a workflow is established to enable the transformation of US tracking data to the coordinates of the treatment delivery or imaging system – even if the US probe is moving due to respiration. It is shown that the US tracking signal is equally adequate for 4D PET image reconstruction as the clinically used respiration belt and provides additional opportunities in this concern. Furthermore, it is demonstrated that the US probe being within the PET field of view generally has no relevant influence on the image quality. The accuracy and precision of all the steps in the calibration workflow for US tracking-based 4D PET imaging are found to be in an acceptable range for clinical implementation. Eventually, we show in vitro that an US-based motion tracking in absolute room coordinates with a moving US transducer is feasible. PMID:26649277

Volumetric Spectroscopic Imaging of Glioblastoma Multiforme Radiation Treatment Volumes

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

Parra, N. Andres; Maudsley, Andrew A.; Gupta, Rakesh K.

Purpose: Magnetic resonance (MR) imaging and computed tomography (CT) are used almost exclusively in radiation therapy planning of glioblastoma multiforme (GBM), despite their well-recognized limitations. MR spectroscopic imaging (MRSI) can identify biochemical patterns associated with normal brain and tumor, predominantly by observation of choline (Cho) and N-acetylaspartate (NAA) distributions. In this study, volumetric 3-dimensional MRSI was used to map these compounds over a wide region of the brain and to evaluate metabolite-defined treatment targets (metabolic tumor volumes [MTV]). Methods and Materials: Volumetric MRSI with effective voxel size of ∼1.0 mL and standard clinical MR images were obtained from 19 GBM patients.more » Gross tumor volumes and edema were manually outlined, and clinical target volumes (CTVs) receiving 46 and 60 Gy were defined (CTV{sub 46} and CTV{sub 60}, respectively). MTV{sub Cho} and MTV{sub NAA} were constructed based on volumes with high Cho and low NAA relative to values estimated from normal-appearing tissue. Results: The MRSI coverage of the brain was between 70% and 76%. The MTV{sub NAA} were almost entirely contained within the edema, and the correlation between the 2 volumes was significant (r=0.68, P=.001). In contrast, a considerable fraction of MTV{sub Cho} was outside of the edema (median, 33%) and for some patients it was also outside of the CTV{sub 46} and CTV{sub 60}. These untreated volumes were greater than 10% for 7 patients (37%) in the study, and on average more than one-third (34.3%) of the MTV{sub Cho} for these patients were outside of CTV{sub 60}. Conclusions: This study demonstrates the potential usefulness of whole-brain MRSI for radiation therapy planning of GBM and revealed that areas of metabolically active tumor are not covered by standard RT volumes. The described integration of MTV into the RT system will pave the way to future clinical trials investigating outcomes in patients treated based

Using an image-extended relational database to support content-based image retrieval in a PACS.

PubMed

Traina, Caetano; Traina, Agma J M; Araújo, Myrian R B; Bueno, Josiane M; Chino, Fabio J T; Razente, Humberto; Azevedo-Marques, Paulo M

2005-12-01

This paper presents a new Picture Archiving and Communication System (PACS), called cbPACS, which has content-based image retrieval capabilities. The cbPACS answers range and k-nearest- neighbor similarity queries, employing a relational database manager extended to support images. The images are compared through their features, which are extracted by an image-processing module and stored in the extended relational database. The database extensions were developed aiming at efficiently answering similarity queries by taking advantage of specialized indexing methods. The main concept supporting the extensions is the definition, inside the relational manager, of distance functions based on features extracted from the images. An extension to the SQL language enables the construction of an interpreter that intercepts the extended commands and translates them to standard SQL, allowing any relational database server to be used. By now, the system implemented works on features based on color distribution of the images through normalized histograms as well as metric histograms. Metric histograms are invariant regarding scale, translation and rotation of images and also to brightness transformations. The cbPACS is prepared to integrate new image features, based on texture and shape of the main objects in the image.

SU-D-BRD-02: A Web-Based Image Processing and Plan Evaluation Platform (WIPPEP) for Future Cloud-Based Radiotherapy

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

Chai, X; Liu, L; Xing, L

Purpose: Visualization and processing of medical images and radiation treatment plan evaluation have traditionally been constrained to local workstations with limited computation power and ability of data sharing and software update. We present a web-based image processing and planning evaluation platform (WIPPEP) for radiotherapy applications with high efficiency, ubiquitous web access, and real-time data sharing. Methods: This software platform consists of three parts: web server, image server and computation server. Each independent server communicates with each other through HTTP requests. The web server is the key component that provides visualizations and user interface through front-end web browsers and relay informationmore » to the backend to process user requests. The image server serves as a PACS system. The computation server performs the actual image processing and dose calculation. The web server backend is developed using Java Servlets and the frontend is developed using HTML5, Javascript, and jQuery. The image server is based on open source DCME4CHEE PACS system. The computation server can be written in any programming language as long as it can send/receive HTTP requests. Our computation server was implemented in Delphi, Python and PHP, which can process data directly or via a C++ program DLL. Results: This software platform is running on a 32-core CPU server virtually hosting the web server, image server, and computation servers separately. Users can visit our internal website with Chrome browser, select a specific patient, visualize image and RT structures belonging to this patient and perform image segmentation running Delphi computation server and Monte Carlo dose calculation on Python or PHP computation server. Conclusion: We have developed a webbased image processing and plan evaluation platform prototype for radiotherapy. This system has clearly demonstrated the feasibility of performing image processing and plan evaluation platform

Mapping Fire Severity Using Imaging Spectroscopy and Kernel Based Image Analysis

NASA Astrophysics Data System (ADS)

Prasad, S.; Cui, M.; Zhang, Y.; Veraverbeke, S.

2014-12-01

Improved spatial representation of within-burn heterogeneity after wildfires is paramount to effective land management decisions and more accurate fire emissions estimates. In this work, we demonstrate feasibility and efficacy of airborne imaging spectroscopy (hyperspectral imagery) for quantifying wildfire burn severity, using kernel based image analysis techniques. Two different airborne hyperspectral datasets, acquired over the 2011 Canyon and 2013 Rim fire in California using the Airborne Visible InfraRed Imaging Spectrometer (AVIRIS) sensor, were used in this study. The Rim Fire, covering parts of the Yosemite National Park started on August 17, 2013, and was the third largest fire in California's history. Canyon Fire occurred in the Tehachapi mountains, and started on September 4, 2011. In addition to post-fire data for both fires, half of the Rim fire was also covered with pre-fire images. Fire severity was measured in the field using Geo Composite Burn Index (GeoCBI). The field data was utilized to train and validate our models, wherein the trained models, in conjunction with imaging spectroscopy data were used for GeoCBI estimation wide geographical regions. This work presents an approach for using remotely sensed imagery combined with GeoCBI field data to map fire scars based on a non-linear (kernel based) epsilon-Support Vector Regression (e-SVR), which was used to learn the relationship between spectra and GeoCBI in a kernel-induced feature space. Classification of healthy vegetation versus fire-affected areas based on morphological multi-attribute profiles was also studied. The availability of pre- and post-fire imaging spectroscopy data over the Rim Fire provided a unique opportunity to evaluate the performance of bi-temporal imaging spectroscopy for assessing post-fire effects. This type of data is currently constrained because of limited airborne acquisitions before a fire, but will become widespread with future spaceborne sensors such as those on

Plenoptic layer-based modeling for image based rendering.

PubMed

Pearson, James; Brookes, Mike; Dragotti, Pier Luigi

2013-09-01

Image based rendering is an attractive alternative to model based rendering for generating novel views because of its lower complexity and potential for photo-realistic results. To reduce the number of images necessary for alias-free rendering, some geometric information for the 3D scene is normally necessary. In this paper, we present a fast automatic layer-based method for synthesizing an arbitrary new view of a scene from a set of existing views. Our algorithm takes advantage of the knowledge of the typical structure of multiview data to perform occlusion-aware layer extraction. In addition, the number of depth layers used to approximate the geometry of the scene is chosen based on plenoptic sampling theory with the layers placed non-uniformly to account for the scene distribution. The rendering is achieved using a probabilistic interpolation approach and by extracting the depth layer information on a small number of key images. Numerical results demonstrate that the algorithm is fast and yet is only 0.25 dB away from the ideal performance achieved with the ground-truth knowledge of the 3D geometry of the scene of interest. This indicates that there are measurable benefits from following the predictions of plenoptic theory and that they remain true when translated into a practical system for real world data.

Automatic x-ray image contrast enhancement based on parameter auto-optimization.

PubMed

Qiu, Jianfeng; Harold Li, H; Zhang, Tiezhi; Ma, Fangfang; Yang, Deshan

2017-11-01

Insufficient image contrast associated with radiation therapy daily setup x-ray images could negatively affect accurate patient treatment setup. We developed a method to perform automatic and user-independent contrast enhancement on 2D kilo voltage (kV) and megavoltage (MV) x-ray images. The goal was to provide tissue contrast optimized for each treatment site in order to support accurate patient daily treatment setup and the subsequent offline review. The proposed method processes the 2D x-ray images with an optimized image processing filter chain, which consists of a noise reduction filter and a high-pass filter followed by a contrast limited adaptive histogram equalization (CLAHE) filter. The most important innovation is to optimize the image processing parameters automatically to determine the required image contrast settings per disease site and imaging modality. Three major parameters controlling the image processing chain, i.e., the Gaussian smoothing weighting factor for the high-pass filter, the block size, and the clip limiting parameter for the CLAHE filter, were determined automatically using an interior-point constrained optimization algorithm. Fifty-two kV and MV x-ray images were included in this study. The results were manually evaluated and ranked with scores from 1 (worst, unacceptable) to 5 (significantly better than adequate and visually praise worthy) by physicians and physicists. The average scores for the images processed by the proposed method, the CLAHE, and the best window-level adjustment were 3.92, 2.83, and 2.27, respectively. The percentage of the processed images received a score of 5 were 48, 29, and 18%, respectively. The proposed method is able to outperform the standard image contrast adjustment procedures that are currently used in the commercial clinical systems. When the proposed method is implemented in the clinical systems as an automatic image processing filter, it could be useful for allowing quicker and potentially more

Video-based noncooperative iris image segmentation.

PubMed

Du, Yingzi; Arslanturk, Emrah; Zhou, Zhi; Belcher, Craig

2011-02-01

In this paper, we propose a video-based noncooperative iris image segmentation scheme that incorporates a quality filter to quickly eliminate images without an eye, employs a coarse-to-fine segmentation scheme to improve the overall efficiency, uses a direct least squares fitting of ellipses method to model the deformed pupil and limbic boundaries, and develops a window gradient-based method to remove noise in the iris region. A remote iris acquisition system is set up to collect noncooperative iris video images. An objective method is used to quantitatively evaluate the accuracy of the segmentation results. The experimental results demonstrate the effectiveness of this method. The proposed method would make noncooperative iris recognition or iris surveillance possible.

SU-F-T-427: Utilization and Evaluation of Diagnostic CT Imaging with MAR Technique for Radiation Therapy Treatment Planning

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

Xu, M; Foster, R; Parks, H

Purpose: The objective was to utilize and evaluate diagnostic CT-MAR technique for radiation therapy treatment planning. Methods: A Toshiba-diagnostic-CT acquisition with SEMAR(Single-energy-MAR)-algorism was performed to make the metal-artifact-reduction (MAR) for patient treatment planning. CT-imaging datasets with and without SEMAR were taken on a Catphan-phantom. Two sets of CT-numbers were calibrated with the relative electron densities (RED). A tissue characterization phantom with Gammex various simulating material rods was used to establish the relationship between known REDs and corresponding CT-numbers. A GE-CT-sim acquisition was taken on the Catphan for comparison. A patient with bilateral hip arthroplasty was scanned in the radiotherapy CT-simmore » and the diagnostic SEMAR-CT on a flat panel. The derived SEMAR images were used as a primary CT dataset to create contours for the target, critical-structures, and for planning. A deformable registration was performed with VelocityAI to track voxel changes between SEMAR and CT-sim images. The SEMAR-CT images with minimal artifacts and high quality of geometrical and spatial integrity were employed for a treatment plan. Treatment-plans were evaluated based on deformable registration of SEMAR-CT and CT-sim dataset with assigned CT-numbers in the metal artifact regions in Eclipse v11 TPS. Results: The RED and CT-number relationships were consistent for the datasets in CT-sim and CT’s with and without SEMAR. SEMAR datasets with high image quality were used for PTV and organ delineation in the treatment planning process. For dose distribution to the PTV through the DVH analysis, the plan using CT-sim with the assigned CT-number showed a good agreement to those on deformable CT-SEMAR. Conclusion: A diagnostic-CT with MAR-algorithm can be utilized for radiotherapy treatment planning with CT-number calibrated to the RED. Treatment planning comparison and DVH shows a good agreement in the PTV and critical organs

Evaluation of GMI and PMI diffeomorphic-based demons algorithms for aligning PET and CT Images.

PubMed

Yang, Juan; Wang, Hongjun; Zhang, You; Yin, Yong

2015-07-08

Fusion of anatomic information in computed tomography (CT) and functional information in 18F-FDG positron emission tomography (PET) is crucial for accurate differentiation of tumor from benign masses, designing radiotherapy treatment plan and staging of cancer. Although current PET and CT images can be acquired from combined 18F-FDG PET/CT scanner, the two acquisitions are scanned separately and take a long time, which may induce potential positional errors in global and local caused by respiratory motion or organ peristalsis. So registration (alignment) of whole-body PET and CT images is a prerequisite for their meaningful fusion. The purpose of this study was to assess the performance of two multimodal registration algorithms for aligning PET and CT images. The proposed gradient of mutual information (GMI)-based demons algorithm, which incorporated the GMI between two images as an external force to facilitate the alignment, was compared with the point-wise mutual information (PMI) diffeomorphic-based demons algorithm whose external force was modified by replacing the image intensity difference in diffeomorphic demons algorithm with the PMI to make it appropriate for multimodal image registration. Eight patients with esophageal cancer(s) were enrolled in this IRB-approved study. Whole-body PET and CT images were acquired from a combined 18F-FDG PET/CT scanner for each patient. The modified Hausdorff distance (d(MH)) was used to evaluate the registration accuracy of the two algorithms. Of all patients, the mean values and standard deviations (SDs) of d(MH) were 6.65 (± 1.90) voxels and 6.01 (± 1.90) after the GMI-based demons and the PMI diffeomorphic-based demons registration algorithms respectively. Preliminary results on oncological patients showed that the respiratory motion and organ peristalsis in PET/CT esophageal images could not be neglected, although a combined 18F-FDG PET/CT scanner was used for image acquisition. The PMI diffeomorphic-based demons

Complex adaptation-based LDR image rendering for 3D image reconstruction

NASA Astrophysics Data System (ADS)

Lee, Sung-Hak; Kwon, Hyuk-Ju; Sohng, Kyu-Ik

2014-07-01

A low-dynamic tone-compression technique is developed for realistic image rendering that can make three-dimensional (3D) images similar to realistic scenes by overcoming brightness dimming in the 3D display mode. The 3D surround provides varying conditions for image quality, illuminant adaptation, contrast, gamma, color, sharpness, and so on. In general, gain/offset adjustment, gamma compensation, and histogram equalization have performed well in contrast compression; however, as a result of signal saturation and clipping effects, image details are removed and information is lost on bright and dark areas. Thus, an enhanced image mapping technique is proposed based on space-varying image compression. The performance of contrast compression is enhanced with complex adaptation in a 3D viewing surround combining global and local adaptation. Evaluating local image rendering in view of tone and color expression, noise reduction, and edge compensation confirms that the proposed 3D image-mapping model can compensate for the loss of image quality in the 3D mode.

Computer-Aided Characterization and Diagnosis of Diffuse Liver Diseases Based on Ultrasound Imaging: A Review.

PubMed

Bharti, Puja; Mittal, Deepti; Ananthasivan, Rupa

2016-04-19

Diffuse liver diseases, such as hepatitis, fatty liver, and cirrhosis, are becoming a leading cause of fatality and disability all over the world. Early detection and diagnosis of these diseases is extremely important to save lives and improve effectiveness of treatment. Ultrasound imaging, a noninvasive diagnostic technique, is the most commonly used modality for examining liver abnormalities. However, the accuracy of ultrasound-based diagnosis depends highly on expertise of radiologists. Computer-aided diagnosis systems based on ultrasound imaging assist in fast diagnosis, provide a reliable "second opinion" for experts, and act as an effective tool to measure response of treatment on patients undergoing clinical trials. In this review, we first describe appearance of liver abnormalities in ultrasound images and state the practical issues encountered in characterization of diffuse liver diseases that can be addressed by software algorithms. We then discuss computer-aided diagnosis in general with features and classifiers relevant to diffuse liver diseases. In later sections of this paper, we review the published studies and describe the key findings of those studies. A concise tabular summary comparing image database, features extraction, feature selection, and classification algorithms presented in the published studies is also exhibited. Finally, we conclude with a summary of key findings and directions for further improvements in the areas of accuracy and objectiveness of computer-aided diagnosis. © The Author(s) 2016.

Improved patch-based learning for image deblurring

NASA Astrophysics Data System (ADS)

Dong, Bo; Jiang, Zhiguo; Zhang, Haopeng

2015-05-01

Most recent image deblurring methods only use valid information found in input image as the clue to fill the deblurring region. These methods usually have the defects of insufficient prior information and relatively poor adaptiveness. Patch-based method not only uses the valid information of the input image itself, but also utilizes the prior information of the sample images to improve the adaptiveness. However the cost function of this method is quite time-consuming and the method may also produce ringing artifacts. In this paper, we propose an improved non-blind deblurring algorithm based on learning patch likelihoods. On one hand, we consider the effect of the Gaussian mixture model with different weights and normalize the weight values, which can optimize the cost function and reduce running time. On the other hand, a post processing method is proposed to solve the ringing artifacts produced by traditional patch-based method. Extensive experiments are performed. Experimental results verify that our method can effectively reduce the execution time, suppress the ringing artifacts effectively, and keep the quality of deblurred image.

Light Field Imaging Based Accurate Image Specular Highlight Removal

PubMed Central

Wang, Haoqian; Xu, Chenxue; Wang, Xingzheng; Zhang, Yongbing; Peng, Bo

2016-01-01

Specular reflection removal is indispensable to many computer vision tasks. However, most existing methods fail or degrade in complex real scenarios for their individual drawbacks. Benefiting from the light field imaging technology, this paper proposes a novel and accurate approach to remove specularity and improve image quality. We first capture images with specularity by the light field camera (Lytro ILLUM). After accurately estimating the image depth, a simple and concise threshold strategy is adopted to cluster the specular pixels into “unsaturated” and “saturated” category. Finally, a color variance analysis of multiple views and a local color refinement are individually conducted on the two categories to recover diffuse color information. Experimental evaluation by comparison with existed methods based on our light field dataset together with Stanford light field archive verifies the effectiveness of our proposed algorithm. PMID:27253083

Case-based fracture image retrieval.

PubMed

Zhou, Xin; Stern, Richard; Müller, Henning

2012-05-01

Case-based fracture image retrieval can assist surgeons in decisions regarding new cases by supplying visually similar past cases. This tool may guide fracture fixation and management through comparison of long-term outcomes in similar cases. A fracture image database collected over 10 years at the orthopedic service of the University Hospitals of Geneva was used. This database contains 2,690 fracture cases associated with 43 classes (based on the AO/OTA classification). A case-based retrieval engine was developed and evaluated using retrieval precision as a performance metric. Only cases in the same class as the query case are considered as relevant. The scale-invariant feature transform (SIFT) is used for image analysis. Performance evaluation was computed in terms of mean average precision (MAP) and early precision (P10, P30). Retrieval results produced with the GNU image finding tool (GIFT) were used as a baseline. Two sampling strategies were evaluated. One used a dense 40 × 40 pixel grid sampling, and the second one used the standard SIFT features. Based on dense pixel grid sampling, three unsupervised feature selection strategies were introduced to further improve retrieval performance. With dense pixel grid sampling, the image is divided into 1,600 (40 × 40) square blocks. The goal is to emphasize the salient regions (blocks) and ignore irrelevant regions. Regions are considered as important when a high variance of the visual features is found. The first strategy is to calculate the variance of all descriptors on the global database. The second strategy is to calculate the variance of all descriptors for each case. A third strategy is to perform a thumbnail image clustering in a first step and then to calculate the variance for each cluster. Finally, a fusion between a SIFT-based system and GIFT is performed. A first comparison on the selection of sampling strategies using SIFT features shows that dense sampling using a pixel grid (MAP = 0

Fast image matching algorithm based on projection characteristics

NASA Astrophysics Data System (ADS)

Zhou, Lijuan; Yue, Xiaobo; Zhou, Lijun

2011-06-01

Based on analyzing the traditional template matching algorithm, this paper identified the key factors restricting the speed of matching and put forward a brand new fast matching algorithm based on projection. Projecting the grayscale image, this algorithm converts the two-dimensional information of the image into one-dimensional one, and then matches and identifies through one-dimensional correlation, meanwhile, because of normalization has been done, when the image brightness or signal amplitude increasing in proportion, it could also perform correct matching. Experimental results show that the projection characteristics based image registration method proposed in this article could greatly improve the matching speed, which ensuring the matching accuracy as well.

Image enhancement based on in vivo hyperspectral gastroscopic images: a case study

NASA Astrophysics Data System (ADS)

Gu, Xiaozhou; Han, Zhimin; Yao, Liqing; Zhong, Yunshi; Shi, Qiang; Fu, Ye; Liu, Changsheng; Wang, Xiguang; Xie, Tianyu

2016-10-01

Hyperspectral imaging (HSI) has been recognized as a powerful tool for noninvasive disease detection in the gastrointestinal field. However, most of the studies on HSI in this field have involved ex vivo biopsies or resected tissues. We proposed an image enhancement method based on in vivo hyperspectral gastroscopic images. First, we developed a flexible gastroscopy system capable of obtaining in vivo hyperspectral images of different types of stomach disease mucosa. Then, depending on a specific object, an appropriate band selection algorithm based on dependence of information was employed to determine a subset of spectral bands that would yield useful spatial information. Finally, these bands were assigned to be the color components of an enhanced image of the object. A gastric ulcer case study demonstrated that our method yields higher color tone contrast, which enhanced the displays of the gastric ulcer regions, and that it will be valuable in clinical applications.

Motion-invariant SRT treatment detection from direct M-scan OCT imaging.

PubMed

Fountoukidou, Tatiana; Raisin, Philippe; Kaufmann, Daniel; Justiz, Jörn; Sznitman, Raphael; Wolf, Sebastian

2018-03-08

Selective retina therapy (SRT) is a laser treatment targeting specific posterior retinal layers. It is focused on inducing damage to the retinal pigment epithelium (RPE), while sparing other retinal tissue compared to traditional photocoagulation. However, the targeted RPE layer is invisible with most imaging modalities and induced SRT lesions cannot be monitored. In this work, imaging scans acquired from an experimental setup that couples the SRT laser beam with an optical coherence tomography (OCT) beam are analyzed in order to evaluate the treatment as they occur. We isolated a small part of the time-resolved scan corresponding to the end of the treatment, for which we have microscopic evidence of the SRT outcome. We then use a convolutional neural network to correspond each scan to the treatment result. We explore which aspects of the scan convey more valuable information for a robust therapy evaluation. By only using this adequately small part, we can achieve an online estimation, while being resilient to eye movement. The available dataset consists of time- resolved OCT scans of 98 ex vivo porcine eyes, treated with different energy levels. The proposed method yields high performance in the task of predicting whether the applied energy was adequate for SRT treatment, by focusing on the immediate OCT signal acquired during treatment time. We propose a strategy toward online noninvasive SRT treatment assessment, able to provide a satisfying evaluation of a treatment status, that therefore could be used for the planning of the treatment continuation.

PET imaging for treatment verification of ion therapy: Implementation and experience at GSI Darmstadt and MGH Boston

NASA Astrophysics Data System (ADS)

Parodi, Katia; Bortfeld, Thomas; Enghardt, Wolfgang; Fiedler, Fine; Knopf, Antje; Paganetti, Harald; Pawelke, Jörg; Shakirin, Georgy; Shih, Helen

2008-06-01

Ion beams offer the possibility of improved conformation of the dose delivered to the tumor with better sparing of surrounding tissue and critical structures in comparison to conventional photon and electron external radiation treatment modalities. Full clinical exploitation of this advantage can benefit from in vivo confirmation of the actual beam delivery and, in particular, of the ion range in the patient. During irradiation, positron emitters like 15O (half-life T1/2≈2 min) and 11C ( T1/2≈20 min) are formed in nuclear interactions between the ions and the tissue. Detection of this transient radioactivity via positron emission tomography (PET) and comparison with the expectation based on the prescribed beam application may serve as an in vivo, non-invasive range validation method of the whole treatment planning and delivery chain. For technical implementation, PET imaging during irradiation (in-beam) requires the development of customized, limited angle detectors with data acquisition synchronized with the beam delivery. Alternatively, commercial PET or PET/CT scanners in close proximity to the treatment site enable detection of the residual activation from long-lived emitters shortly after treatment (offline). This paper reviews two clinical examples using a dedicated in-beam PET scanner for verification of carbon ion therapy at GSI Darmstadt, Germany, as well as a commercial offline PET/CT tomograph for post-radiation imaging of proton treatments at Massachusetts General Hospital, Boston, USA. Challenges as well as pros and cons of the two imaging approaches in dependence of the different ion type and beam delivery system are discussed.

Target Identification Using Harmonic Wavelet Based ISAR Imaging

NASA Astrophysics Data System (ADS)

Shreyamsha Kumar, B. K.; Prabhakar, B.; Suryanarayana, K.; Thilagavathi, V.; Rajagopal, R.

2006-12-01

A new approach has been proposed to reduce the computations involved in the ISAR imaging, which uses harmonic wavelet-(HW) based time-frequency representation (TFR). Since the HW-based TFR falls into a category of nonparametric time-frequency (T-F) analysis tool, it is computationally efficient compared to parametric T-F analysis tools such as adaptive joint time-frequency transform (AJTFT), adaptive wavelet transform (AWT), and evolutionary AWT (EAWT). Further, the performance of the proposed method of ISAR imaging is compared with the ISAR imaging by other nonparametric T-F analysis tools such as short-time Fourier transform (STFT) and Choi-Williams distribution (CWD). In the ISAR imaging, the use of HW-based TFR provides similar/better results with significant (92%) computational advantage compared to that obtained by CWD. The ISAR images thus obtained are identified using a neural network-based classification scheme with feature set invariant to translation, rotation, and scaling.

Retinal imaging analysis based on vessel detection.

PubMed

Jamal, Arshad; Hazim Alkawaz, Mohammed; Rehman, Amjad; Saba, Tanzila

2017-07-01

With an increase in the advancement of digital imaging and computing power, computationally intelligent technologies are in high demand to be used in ophthalmology cure and treatment. In current research, Retina Image Analysis (RIA) is developed for optometrist at Eye Care Center in Management and Science University. This research aims to analyze the retina through vessel detection. The RIA assists in the analysis of the retinal images and specialists are served with various options like saving, processing and analyzing retinal images through its advanced interface layout. Additionally, RIA assists in the selection process of vessel segment; processing these vessels by calculating its diameter, standard deviation, length, and displaying detected vessel on the retina. The Agile Unified Process is adopted as the methodology in developing this research. To conclude, Retina Image Analysis might help the optometrist to get better understanding in analyzing the patient's retina. Finally, the Retina Image Analysis procedure is developed using MATLAB (R2011b). Promising results are attained that are comparable in the state of art. © 2017 Wiley Periodicals, Inc.

Deep Convolutional Neural Network-Based Early Automated Detection of Diabetic Retinopathy Using Fundus Image.

PubMed

Xu, Kele; Feng, Dawei; Mi, Haibo

2017-11-23

The automatic detection of diabetic retinopathy is of vital importance, as it is the main cause of irreversible vision loss in the working-age population in the developed world. The early detection of diabetic retinopathy occurrence can be very helpful for clinical treatment; although several different feature extraction approaches have been proposed, the classification task for retinal images is still tedious even for those trained clinicians. Recently, deep convolutional neural networks have manifested superior performance in image classification compared to previous handcrafted feature-based image classification methods. Thus, in this paper, we explored the use of deep convolutional neural network methodology for the automatic classification of diabetic retinopathy using color fundus image, and obtained an accuracy of 94.5% on our dataset, outperforming the results obtained by using classical approaches.

Image-based informatics for Preclinical Biomedical Research

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

Tobin Jr, Kenneth William; Aykac, Deniz; Price, Jeffery R

2006-01-01

In 2006, the New England Journal of Medicine selected medical imaging as one of the eleven most important innovations of the past 1,000 years, primarily due to its ability to allow physicians and researchers to visualize the very nature of disease. As a result of the broad-based adoption of micro imaging technologies, preclinical researchers today are generating terabytes of image data from both anatomic and functional imaging modes. In this paper we describe our early research to apply content-based image retrieval to index and manage large image libraries generated in the study of amyloid disease in mice. Amyloidosis is associatedmore » with diseases such as Alzheimer's, type 2 diabetes, and myeloma. In particular, we will focus on results to date in the area of small animal organ segmentation and description for CT, SPECT, and PET modes and present a small set of preliminary retrieval results for a specific disease state in kidney CT cross-sections.« less

Image-based Informatics for Preclinical Biomedical Research

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

Tobin Jr, Kenneth William; Aykac, Deniz; Muthusamy Govindasamy, Vijaya Priya

2006-01-01

In 2006, the New England Journal of Medicine selected medical imaging as one of the eleven most important innovations of the past 1,000 years, primarily due to its ability to allow physicians and researchers to visualize the very nature of disease. As a result of the broad-based adoption of micro imaging technologies, preclinical researchers today are generating terabytes of image data from both anatomic and functional imaging modes. In this paper we describe our early research to apply content-based image retrieval to index and manage large image libraries generated in the study of amyloid disease in mice. Amyloidosis is associatedmore » with diseases such as Alzheimer's, type 2 diabetes, chronic inflammation and myeloma. In particular, we will focus on results to date in the area of small animal organ segmentation and description for CT, SPECT, and PET modes and present a small set of preliminary retrieval results for a specific disease state in kidney CT crosssections.« less

CH3NH3PbI3 based solar cell: Modified by antisolvent treatment

NASA Astrophysics Data System (ADS)

Nandi, Pronoy; Giri, Chandan; Bansode, Umesh; Topwal, D.

2017-05-01

Solar cells based on new class of organic inorganic hybrid perovskite CH3NH3PbI3 were prepared by Ethyl acetate (EA); antisolvent treatment for the first time. This treatment results in new morphology for CH3NH3PbI3 thin film. FESEM image shows microrod type structures of CH3NH3PbI3 after EA antisolvent treatment. Energy band diagram was constructed using photoluminescence and photoemission studies. A better power conversion efficiency was achieved in EA treated film compare to without EA treated film.

Supervoxels for Graph Cuts-Based Deformable Image Registration Using Guided Image Filtering

PubMed Central

Szmul, Adam; Papież, Bartłomiej W.; Hallack, Andre; Grau, Vicente; Schnabel, Julia A.

2017-01-01

In this work we propose to combine a supervoxel-based image representation with the concept of graph cuts as an efficient optimization technique for 3D deformable image registration. Due to the pixels/voxels-wise graph construction, the use of graph cuts in this context has been mainly limited to 2D applications. However, our work overcomes some of the previous limitations by posing the problem on a graph created by adjacent supervoxels, where the number of nodes in the graph is reduced from the number of voxels to the number of supervoxels. We demonstrate how a supervoxel image representation, combined with graph cuts-based optimization can be applied to 3D data. We further show that the application of a relaxed graph representation of the image, followed by guided image filtering over the estimated deformation field, allows us to model ‘sliding motion’. Applying this method to lung image registration, results in highly accurate image registration and anatomically plausible estimations of the deformations. Evaluation of our method on a publicly available Computed Tomography lung image dataset (www.dir-lab.com) leads to the observation that our new approach compares very favorably with state-of-the-art in continuous and discrete image registration methods achieving Target Registration Error of 1.16mm on average per landmark. PMID:29225433

A statistical model of catheter motion from interventional x-ray images: application to image-based gating

NASA Astrophysics Data System (ADS)

Panayiotou, M.; King, A. P.; Ma, Y.; Housden, R. J.; Rinaldi, C. A.; Gill, J.; Cooklin, M.; O'Neill, M.; Rhode, K. S.

2013-11-01

The motion and deformation of catheters that lie inside cardiac structures can provide valuable information about the motion of the heart. In this paper we describe the formation of a novel statistical model of the motion of a coronary sinus (CS) catheter based on principal component analysis of tracked electrode locations from standard mono-plane x-ray fluoroscopy images. We demonstrate the application of our model for the purposes of retrospective cardiac and respiratory gating of x-ray fluoroscopy images in normal dose x-ray fluoroscopy images, and demonstrate how a modification of the technique allows application to very low dose scenarios. We validated our method on ten mono-plane imaging sequences comprising a total of 610 frames from ten different patients undergoing radiofrequency ablation for the treatment of atrial fibrillation. For normal dose images we established systole, end-inspiration and end-expiration gating with success rates of 100%, 92.1% and 86.9%, respectively. For very low dose applications, the method was tested on the same ten mono-plane x-ray fluoroscopy sequences without noise and with added noise at signal to noise ratio (SNR) values of √50, √10, √8, √6, √5, √2 and √1 to simulate the image quality of increasingly lower dose x-ray images. The method was able to detect the CS catheter even in the lowest SNR images with median errors not exceeding 2.6 mm per electrode. Furthermore, gating success rates of 100%, 71.4% and 85.7% were achieved at the low SNR value of √2, representing a dose reduction of more than 25 times. Thus, the technique has the potential to extract useful information whilst substantially reducing the radiation exposure.

Speckle noise reduction in ultrasound images using a discrete wavelet transform-based image fusion technique.

PubMed

Choi, Hyun Ho; Lee, Ju Hwan; Kim, Sung Min; Park, Sung Yun

2015-01-01

Here, the speckle noise in ultrasonic images is removed using an image fusion-based denoising method. To optimize the denoising performance, each discrete wavelet transform (DWT) and filtering technique was analyzed and compared. In addition, the performances were compared in order to derive the optimal input conditions. To evaluate the speckle noise removal performance, an image fusion algorithm was applied to the ultrasound images, and comparatively analyzed with the original image without the algorithm. As a result, applying DWT and filtering techniques caused information loss and noise characteristics, and did not represent the most significant noise reduction performance. Conversely, an image fusion method applying SRAD-original conditions preserved the key information in the original image, and the speckle noise was removed. Based on such characteristics, the input conditions of SRAD-original had the best denoising performance with the ultrasound images. From this study, the best denoising technique proposed based on the results was confirmed to have a high potential for clinical application.

Identifying Medical Diagnoses and Treatable Diseases by Image-Based Deep Learning.