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Sample records for atypical imaging features

  1. Atypical magnetic resonance imaging features in subacute sclerosing panencephalitis

    PubMed Central

    Das, Biplab; Goyal, Manoj Kumar; Modi, Manish; Mehta, Sahil; Chakravarthi, Sudheer; Lal, Vivek; Vyas, Sameer

    2016-01-01

    Objectives: Subacute sclerosing panencephalitis (SSPE) is rare chronic, progressive encephalitis that affects primarily children and young adults, caused by a persistent infection with measles virus. No cure for SSPE exists, but the condition can be managed by medication if treatment is started at an early stage. Methods and Results: Heterogeneity of imaging findings in SSPE is not very uncommon. But pial and gyral enhancements are very rarely noticed. Significant asymmetric onset as well as pial-gyral enhancements is not reported. Herein we present a case of 16 years adolescent of SSPE having remarkable asymmetric pial-gyral enhancements, which were misinterpreted as tubercular infection. Conclusion: Early diagnosis and treatment is encouraging in SSPE, although it is not curable with current therapy. Clinico-radiological and electrophysiological correlation is very important in diagnosis of SSPE, more gravely in patients having atypical image findings as in our index case. PMID:27293348

  2. Pilocytic astrocytoma presenting with atypical features on magnetic resonance imaging.

    PubMed

    Nakano, Yoshiteru; Yamamoto, Junkoh; Takahashi, Mayu; Soejima, Yoshiteru; Akiba, Daisuke; Kitagawa, Takehiro; Ueta, Kunihiro; Miyaoka, Ryo; Umemura, Takeru; Nishizawa, Shigeru

    2015-10-01

    Pilocytic astrocytoma, which is classified as a grade I astrocytic tumor by the World Health Organization, is the most common type of glioma in children and young adults. Pilocytic astrocytoma generally appears as a well-circumscribed, contrast-enhancing lesion, frequently with cystic components on magnetic resonance imaging (MRI). However, it has been reported that the MRI appearance of pilocytic astrocytoma may be similar to that of high-grade gliomas in some cases. We here report on 6 cases of pilocytic astrocytoma with atypical MRI findings, including small cyst formation, heterogeneously enhancing tumor nodules, irregularly enhancing tumor nodules, and enhancing tumor nodules with internal hemorrhage. All tumors were successfully resected, and the histological diagnoses were pilocytic astrocytoma. When the tumor is located near a cerebral cistern or ventricle, the risk of leptomeningeal dissemination is increased. Furthermore, partial resection has also been associated with a higher risk of recurrence and leptomeningeal dissemination. To date, all but one patient are alive and recurrence-free. Because the preoperative diagnosis influences the decision on the extent of resection and because of the high risk of leptomeningeal dissemination associated with these tumors, careful and correct diagnosis by MRI is important. PMID:25454397

  3. Atypical Imaging Features of Tuberculous Spondylitis: Case Report with Literature Review

    PubMed Central

    Momjian, Rita; George, Mina

    2014-01-01

    Spinal tuberculosis in its typical form that shows destruction of two adjacent vertebral bodies and opposing end plates, destruction of the intervening intervertebral disc and a paravertebral or psoas abscess, is easily recognized and readily treated. Atypical tuberculous spondylitis without the above mentioned imaging features, although seen infrequently, has been well documented. We present, in this report, a case of atypical tuberculous spondylitis showing involvement of contiguous lower dorsal vertebral bodies and posterior elements with paravertebral and epidural abscess but with preserved intervertebral discs. The patient presented in advanced stage with progressive severe neurological symptoms due to spinal cord compression. Non-enhanced magnetic resonance imaging led to misdiagnosis of the lesion as a neoplastic process. It was followed by contrast enhanced computed tomography of the chest and abdomen that raised the possibility of an infectious process and, post-operatively, histopathological examination of the operative specimen confirmed tuberculosis. This case indicates the difficulty in differentiating atypical spinal tuberculosis from other diseases causing spinal cord compression. The different forms of atypical tuberculous spondylitis reported in the literature are reviewed. The role of the radiologist in tuberculous spondylitis is not only to recognize the imaging characteristics of the disease by best imaging modality, which is contrast enhanced magnetic resonance imaging, but also to be alert to the more atypical presentations to ensure early diagnosis and prompt treatment to prevent complications. However, when neither clinical examination nor magnetic resonance imaging findings are reliable in differentiating spinal infection from one another and from neoplasm, adequate biopsy, either imaging guided or surgical biopsy is essential for early diagnosis. PMID:25926906

  4. Atypical teratoid/rhabdoid tumors in adult patients: CT and MR imaging features.

    PubMed

    Han, L; Qiu, Y; Xie, C; Zhang, J; Lv, X; Xiong, W; Wang, W; Zhang, X; Wu, P

    2011-01-01

    Primary AT/RT is a rare highly malignant tumor of the CNS, usually occurring in children younger than 5 years of age. The objective of this study was to characterize the CT and MR imaging findings in a series of 5 adult patients with pathologically proved AT/RT. All 5 AT/RTs were supratentorial. In 2 patients who underwent nonenhanced CT, the tumors appeared isoattenuated, and 1 of the 2 tumors contained calcifications. Solid portions of the tumors on MR imaging were isointense on T1-weighted, T2-weighted, and FLAIR images, and 1 case showed restricted diffusion on DWI. The tumors also demonstrated a bandlike rim of strong enhancement surrounding a central cystic area on contrast-enhanced T1-weighted imaging. One tumor was associated with destruction of the calvaria. Although AT/RTs can have nonspecific findings, the tumors in our series were large and isointense on T1-weighted, T2-weighted, and FLAIR images with central necrosis and prominent rim enhancement. PMID:21051520

  5. Uremic parkinsonism with atypical phenotypes and radiologic features.

    PubMed

    Yoon, Jee-Eun; Kim, Ji Sun; Park, Jeong-Ho; Lee, Kyung-Bok; Roh, Hakjae; Park, Sung Tae; Cho, Jin Whan; Ahn, Moo-Young

    2016-04-01

    Uremic encephalopathy with bilateral basal ganglia lesions has been reported as an acute neurometabolic disease which shows reversible clinical course and brain imaging features. The exact nature and pathophysiology have not been well established. We encountered two patients who showed a relapsing and aggravating course and an atypical phenotype including parkinsonism with paroxysmal dystonic head tremor and acute onset monoparesis of the lower extremity. They also showed unusual radiological findings which revealed combined lesions in the basal ganglia and cortex, persistent hemorrhagic transformation, and focal ischemic lesion in the internal capsule. Herein, we present the unusual phenomenology with atypical radiologic findings and suggest the possible multifactorial pathogenesis of uremic encephalopathy. PMID:26631408

  6. Atypical and ischemic features of embolized meningiomas.

    PubMed

    Matsuda, Ken; Takeuchi, Hiroaki; Arai, Yoshikazu; Kitai, Ryuhei; Hosoda, Tetsuya; Tsunetoshi, Kenzo; Arishima, Hidetaka; Sato, Kazufumi; Kikuta, Ken-Ichiro

    2012-01-01

    Preoperative embolization (POE) of meningiomas is widely used to facilitate surgical removal and to reduce intraoperative blood loss. The resulting necrosis and enhanced proliferation have been reported to affect subsequent histologic grading. However, there was little concern about ischemic features, for example small cells resembling atypical meningiomas, cytoplasmic vacuoles resembling clear cell meningioma, intercellular discohesion resembling rhabdoid meningioma, and perivascular cuffs resembling papillary meningioma. Therefore, the extent of these ischemic features was scored and Ki-67 staining indices were investigated in a POE group composed of 29 specimens of meningiomas treated with POE and compared with equivalent results for a non-POE group composed of 29 meningiomas that were not treated with POE. Small cells with high N/C ratios, cytoplasmic vacuoles, intercellular discohesion, and perivascular cuffs were significantly increased in the POE group (versus the non-POE group, p < 0.05). There were no significant differences of the Ki-67 index between the POE group (2.2%) and the non-POE group (1.9%) (p = 0.49). Our results suggest that small cell change resulting in necrosis may be followed by POE, and that clear cell-like, rhabdoid cell-like, or pseudopapillary pattern identified in meningiomas may also be induced by POE. Therefore, histological findings and determination of grading should be evaluated cautiously in cases of embolized meningiomas. PMID:21789536

  7. Depression With Atypical Features: Diagnostic Validity, Prevalence, and Treatment.

    PubMed

    Quitkin, Frederic M.

    2002-06-01

    Depression with atypical features is a treatable and relatively common disorder among depressed outpatients. A growing body of evidence suggests this is a biologically distinct subtype of depression. This assertion is supported by genetic epidemiologic studies and by a preferential response of the subtype to monoamine oxidase inhibitors compared with tricyclic antidepressants. The Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) includes atypical features as a parenthetical modifier for depressive illness. According to DSM-IV diagnostic criteria ("atypical features" specifier), the disorder is primarily characterized by 2 or more of the following symptoms as predominant features in patients with major depression or dysthymic disorder: overeating, oversleeping, "leaden paralysis," and interpersonal rejection sensitivity. Patients also show mood reactivity in response to actual or potential positive events. Despite aspects of the disorder resembling a maladaptive, persistent mode of behavior, patients diagnosed with depression with atypical features demonstrate a good response to antidepressant treatment. PMID:15014736

  8. Imaging of atypical hemangiomas of the liver with pathologic correlation.

    PubMed

    Vilgrain, V; Boulos, L; Vullierme, M P; Denys, A; Terris, B; Menu, Y

    2000-01-01

    Compared with the imaging features of typical hepatic hemangiomas, the imaging features of atypical hepatic hemangiomas have not been well studied or well described. Knowledge of the entire spectrum of atypical hepatic hemangiomas is important and can help one avoid most diagnostic errors. A frequent type of atypical hepatic hemangioma is a lesion with an echoic border at ultrasonography. Less frequent types are large, heterogeneous hemangiomas; rapidly filling hemangiomas; calcified hemangiomas; hyalinized hemangiomas; cystic or multilocular hemangiomas; hemangiomas with fluid-fluid levels; and pedunculated hemangiomas. Adjacent abnormalities consist of arterial-portal venous shunt, capsular retraction, and surrounding nodular hyperplasia; hemangiomas can also develop in cases of fatty liver infiltration. Associated lesions include multiple hemangiomas, hemangiomatosis, focal nodular hyperplasia, and angiosarcoma. Types of atypical evolution are hemangiomas enlarging over time and hemangiomas appearing during pregnancy. Complications consist of inflammation, Kasabach-Merritt syndrome, intratumoral hemorrhage, hemoperitoneum, volvulus, and compression of adjacent structures. In some cases, such as large heterogeneous hemangiomas, calcified hemangiomas, pedunculated hemangiomas, or hemangiomas developing in diffuse fatty liver, a specific diagnosis can be established with imaging, especially magnetic resonance imaging. However, in other atypical cases, the diagnosis will remain uncertain at imaging, and these cases will require histopathologic examination. PMID:10715338

  9. Treating DSM-IV depression with atypical features.

    PubMed

    Stewart, Jonathan W; Thase, Michael E

    2007-04-01

    Depression with atypical features is characterized by mood reactivity and 2 or more symptoms of vegetative reversal (including overeating, oversleeping, severe fatigue or leaden paralysis, and a history of rejection sensitivity). Another important feature of atypical depression is its preferential response to monoamine oxidase inhibitor (MAOI) treatment, especially phenelzine, relative to tricyclic antidepressants (TCAs). The efficacy of newer agents relative to MAOIs and TCAs is unclear. This presentation reviews currently available treatments for DSM-IV depression with atypical features, focusing specifically on placebo-controlled trials. Although phenelzine shows the most efficacy in this population, treatment with TCAs, selective serotonin reuptake inhibitors, cognitive-behavioral therapy, MAOIs other than phenelzine, and other agents are discussed. Following this presentation is a discussion on the treatment of depression with atypical features by experts in this subject area. PMID:17474800

  10. Acute hemorrhagic leukoencephalitis with atypical features.

    PubMed

    Catalan, Mauro; Naccarato, Marcello; Grandi, Fabio Chiodo; Capozzoli, Francesca; Koscica, Nadia; Pizzolato, Gilberto

    2009-02-01

    Acute hemorrhagic leukoencephalitis (AHL) is a rare demyelinating disease mainly affecting children, characterized by acute onset, progressive course and high mortality. A 62-year-old man was admitted to our Unit for diplopia and ataxia ensuing 2 weeks after the onset of pneumonia. MRI T2-weighted images showed signal hyperintensities in the brainstem. Antibodies against Mycoplasma Pneumoniae and cold agglutinins were found. Two weeks later the patient had a worsening of his conditions: he developed left hemiplegia with motor focal seizures and the day after he was deeply comatose (GCS = 4). A second MRI scan showed extensive hyperintensities involving the whole right hemisphere white matter with a small parietal hemorrhagic area. The clinical and neuroimaging features suggested the diagnosis of AHL, Aciclovir in association with steroid therapy were administered and then plasmapheresis was started. After 30 days of coma, the patient gradually reacquired consciousness and motor functions; anyway a left hemiplegia persisted. PMID:19145402

  11. Transformation of a meningioma with atypical imaging

    PubMed Central

    Kumar, Ashish; Deopujari, Chandrashekhar; Karmarkar, Vikram

    2016-01-01

    Meningiomas are benign tumors of the central nervous system. They have long term curability if they are excised completely. If not, they can recur after a prolonged period and can lead to increased morbidity during re-surgery. Recurrence is rarely associated with invasiveness. Usually de-differentiation in case of meningiomas is uncommon without any predisposing factors including different genetic mutations or radiation to the involved region. We report a case of a 38-year-old female who was operated for a benign para-sagittal meningioma 8 years back and subsequently developed an invasive recurrence off late. Also this time, the imaging morphology was slightly different for a meningioma and gross as well as microscopic findings were very atypical. Awareness for such cases must be there while dealing with recurrent meningiomas as invasiveness may not always be associated with adverse predisposing factors like radiation. As invasiveness is always a histopathological diagnosis, picking up such features on imaging is a daunting task and if done, can help neurosurgeons prognosticate such invasive recurrences in a better fashion. PMID:27366271

  12. Transformation of a meningioma with atypical imaging.

    PubMed

    Kumar, Ashish; Deopujari, Chandrashekhar; Karmarkar, Vikram

    2016-01-01

    Meningiomas are benign tumors of the central nervous system. They have long term curability if they are excised completely. If not, they can recur after a prolonged period and can lead to increased morbidity during re-surgery. Recurrence is rarely associated with invasiveness. Usually de-differentiation in case of meningiomas is uncommon without any predisposing factors including different genetic mutations or radiation to the involved region. We report a case of a 38-year-old female who was operated for a benign para-sagittal meningioma 8 years back and subsequently developed an invasive recurrence off late. Also this time, the imaging morphology was slightly different for a meningioma and gross as well as microscopic findings were very atypical. Awareness for such cases must be there while dealing with recurrent meningiomas as invasiveness may not always be associated with adverse predisposing factors like radiation. As invasiveness is always a histopathological diagnosis, picking up such features on imaging is a daunting task and if done, can help neurosurgeons prognosticate such invasive recurrences in a better fashion. PMID:27366271

  13. Atypical Intracranial Epidermoid Cysts: Rare Anomalies with Unique Radiological Features

    PubMed Central

    Law, Eric K. C.; Lee, Ryan K. L.; Ng, Alex W. H.; Siu, Deyond Y. W.; Ng, Ho-Keung

    2015-01-01

    Epidermoid cysts are benign slow growing extra-axial tumours that insinuate between brain structures, while their occurrences in intra-axial or intradiploic locations are exceptionally rare. We present the clinical, imaging, and pathological findings in two patients with atypical epidermoid cysts. CT and MRI findings for the first case revealed an intraparenchymal epidermoid cyst that demonstrated no restricted diffusion. The second case demonstrated an aggressive epidermoid cyst that invaded into the intradiploic spaces, transverse sinus, and the calvarium. The timing of ectodermal tissue sequestration during fetal development may account for the occurrence of atypical epidermoid cysts. PMID:25667778

  14. Clinical features of Friedreich's ataxia: classical and atypical phenotypes.

    PubMed

    Parkinson, Michael H; Boesch, Sylvia; Nachbauer, Wolfgang; Mariotti, Caterina; Giunti, Paola

    2013-08-01

    One hundred and fifty years since Nikolaus Friedreich's first description of the degenerative ataxic syndrome which bears his name, his description remains at the core of the classical clinical phenotype of gait and limb ataxia, poor balance and coordination, leg weakness, sensory loss, areflexia, impaired walking, dysarthria, dysphagia, eye movement abnormalities, scoliosis, foot deformities, cardiomyopathy and diabetes. Onset is typically around puberty with slow progression and shortened life-span often related to cardiac complications. Inheritance is autosomal recessive with the vast majority of cases showing an unstable intronic GAA expansion in both alleles of the frataxin gene on chromosome 9q13. A small number of cases are caused by a compound heterozygous expansion with a point mutation or deletion. Understanding of the underlying molecular biology has enabled identification of atypical phenotypes with late onset, or atypical features such as retained reflexes. Late-onset cases tend to have slower progression and are associated with smaller GAA expansions. Early-onset cases tend to have more rapid progression and a higher frequency of non-neurological features such as diabetes, cardiomyopathy, scoliosis and pes cavus. Compound heterozygotes, including those with large deletions, often have atypical features. In this paper, we review the classical and atypical clinical phenotypes of Friedreich's ataxia. PMID:23859346

  15. The validity of major depression with atypical features based on a community study.

    PubMed

    Horwath, E; Johnson, J; Weissman, M M; Hornig, C D

    1992-10-01

    This article reports on evidence for the validity of major depression (MDD) with atypical features (defined as overeating and oversleeping) as a distinct subtype based on cross-sectional and 1-year prospective data from the Epidemiologic Catchment Area study. MDD with atypical features, when compared to MDD without atypical features, was associated with a younger age of onset, more psychomotor slowing, and more comorbid panic disorder, drug abuse or dependence, and somatization disorder. These differences could not be explained by differences in demographic characteristics or by symptom severity. This study, based on a community sample, found that major depression with atypical features may constitute a distinct subtype. PMID:1447429

  16. Imaging appearances of atypical hydatid cysts

    PubMed Central

    Malik, Amita; Chandra, Ranjan; Prasad, Rajni; Khanna, Geetika; Thukral, Brij B

    2016-01-01

    Hydatid disease continues to be a significant health problem in many parts of the world. It can occur in any part of the body, but liver is the commonest site of involvement. The disease may remain asymptomatic for years. Symptoms occur due to compression of local structures or complications like rupture and infection. The diagnosis is clear when typical radiological appearance is observed at the common sites of involvement. Complications give rise to atypical appearances. These coupled with unusual localizations pose diagnostic difficulty. The aim of this pictorial essay is to demonstrate the atypical manifestations of hydatid cysts – atypical either due to complications or the unusual site. PMID:27081221

  17. Gangliocytic Paraganglioma With Atypical Immunohistochemical Features Presenting as Extrahepatic Biliary Obstruction.

    PubMed

    Sharma, Saniya; Gaspar, Balan Louis; Kumar, Pradeep; Yadav, Thakur Deen; Vasishta, Rakesh Kumar

    2015-10-01

    Gangliocytic paraganglioma is a rare benign tumor of upper gastrointestinal tract that most commonly involves the second part of duodenum. The tumor is detected incidentally on imaging in most of the cases. However, presentation with extrahepatic biliary obstruction is extremely rare. We recently encountered a 50-year-old male patient who was evaluated for extrahepatic biliary obstruction and was found to have a periampullary mass on imaging. The patient underwent pylorus-preserving pancreaticoduodenectomy along with liver biopsy and hepatoduodenal lymph node dissection. On histopathological examination, a tumor was detected in the periampullary region of duodenum, which was confirmed to be gangliocytic paraganglioma on immunohistochemistry along with atypical histological and immunohistochemical features. PMID:26081293

  18. Atypical radiographic features of skull base cholesterol granuloma.

    PubMed

    Dinh, Christine T; Goncalves, Stefania; Bhatia, Rita; Truong, Kim; Telischi, Fred; Angeli, Simon; Morcos, Jacques; Eshraghi, Adrien A

    2016-06-01

    Cholesterol granulomas (CGs) are the most common benign lesions of the petrous apex (PA) and have distinct computed tomography (CT) and magnetic resonance imaging (MRI) characteristics. On CT, CGs of the PA (PACG) present as expansile lesions with erosion of bony trabeculae. MRI shows a hyperintense lesion on T1-and T2-weighted images and do not enhance with gadolinium. The objective is to describe the radiographic features of CGs of the skull base that do not arise from the PA. This study is a retrospective review. Three patients were operated on for suspected recurrent endolymphatic sac tumor, intracranial cholesteatoma, and recurrent sphenoid wing meningioma based on CT and MRI findings. Pathology results were consistent with CG in all three cases. All patients had bone erosion on CT. These skull base CGs did not demonstrate similar MRI features. These lesions were hyperintense, iso-to-hyperintense, and hypointense on T1-weighted MRI, respectively. These CGs were hyperintense in two cases and iso-to-hyperintense in one case on T2-weighted MRI. These lesions either demonstrated central or rim enhancement after gadolinium administration. Skull base CGs that do not arise from the PA demonstrate a broad spectrum of radiographic characteristics on MRI that are not typical of PACG. PMID:26164292

  19. Multispectral Image Feature Points

    PubMed Central

    Aguilera, Cristhian; Barrera, Fernando; Lumbreras, Felipe; Sappa, Angel D.; Toledo, Ricardo

    2012-01-01

    This paper presents a novel feature point descriptor for the multispectral image case Far-Infrared and Visible Spectrum images. It allows matching interest points on images of the same scene but acquired in different spectral bands. Initially, points of interest are detected on both images through a SIFT-like based scale space representation. Then, these points are characterized using an Edge Oriented Histogram (EOH) descriptor. Finally, points of interest from multispectral images are matched by finding nearest couples using the information from the descriptor. The provided experimental results and comparisons with similar methods show both the validity of the proposed approach as well as the improvements it offers with respect to the current state-of-the-art.

  20. Seizures as an Atypical Feature of Beal's Syndrome.

    PubMed

    Jaman, Nazreen B K; Al-Sayegh, Abeer

    2016-08-01

    Congenital contractural arachnodactyly, commonly known as Beal's syndrome, is an extremely rare genetic disorder caused by mutations in the fibrillin-2 (FBN2) gene located on chromosome 5q23. It is an autosomal dominant inherited connective tissue disorder characterised by a Marfan-like body habitus, contractures, abnormally shaped ears and kyphoscoliosis. We report a seven-year-old Omani male who presented to the Sultan Qaboos University Hospital, Muscat, Oman, in 2014 with seizures. He was noted to have certain distinctive facial features and musculoskeletal manifestations; he was subsequently diagnosed with Beal's syndrome. Sequencing of the FBN2 gene revealed that the patient had a novel mutation which was also present in his mother; however, she had only a few facial features indicative of Beal's syndrome and no systemic involvement apart from a history of childhood seizures. To the best of the authors' knowledge, this is the first report of Beal's syndrome with seizure symptoms as a potential feature. PMID:27606123

  1. Toxic leukoencephalopathy with atypical MRI features following a lacquer thinner fire.

    PubMed

    Kao, Hung-Wen; Pare, Laura; Kim, Ronald; Hasso, Anton N

    2014-05-01

    Toxic leukoencephalopathy is a structural alteration of the white matter following exposure to various toxic agents. We report a 49-year-old man exposed to an explosion of lacquer thinner with brain MRI features atypical from those of chronic toxic solvent intoxication. PMID:24291481

  2. Seizures as an Atypical Feature of Beal’s Syndrome

    PubMed Central

    Jaman, Nazreen B. K.; Al-Sayegh, Abeer

    2016-01-01

    Congenital contractural arachnodactyly, commonly known as Beal’s syndrome, is an extremely rare genetic disorder caused by mutations in the fibrillin-2 (FBN2) gene located on chromosome 5q23. It is an autosomal dominant inherited connective tissue disorder characterised by a Marfan-like body habitus, contractures, abnormally shaped ears and kyphoscoliosis. We report a seven-year-old Omani male who presented to the Sultan Qaboos University Hospital, Muscat, Oman, in 2014 with seizures. He was noted to have certain distinctive facial features and musculoskeletal manifestations; he was subsequently diagnosed with Beal’s syndrome. Sequencing of the FBN2 gene revealed that the patient had a novel mutation which was also present in his mother; however, she had only a few facial features indicative of Beal’s syndrome and no systemic involvement apart from a history of childhood seizures. To the best of the authors’ knowledge, this is the first report of Beal’s syndrome with seizure symptoms as a potential feature. PMID:27606123

  3. The high prevalence of "soft" bipolar (II) features in atypical depression.

    PubMed

    Perugi, G; Akiskal, H S; Lattanzi, L; Cecconi, D; Mastrocinque, C; Patronelli, A; Vignoli, S; Bemi, E

    1998-01-01

    Seventy-two percent of 86 major depressive patients with atypical features as defined by the DSM-IV and evaluated systematically were found to meet our criteria for bipolar II and related "soft" bipolar disorders; nearly 60% had antecedent cyclothymic or hyperthymic temperaments. The family history for bipolar disorder validated these clinical findings. Even if we limit the diagnosis of bipolar II to the official DSM-IV threshold of 4 days of hypomania, 32.6% of atypical depressives in our sample would meet this conservative threshold, a rate that is three times higher than the estimates of bipolarity among atypical depressives in the literature. By definition, mood reactivity was present in all patients, while interpersonal sensitivity occurred in 94%. Lifetime comorbidity rates were as follows: social phobia 30%, body dysmorphic disorder 42%, obsessive-compulsive disorder 20%, and panic disorder (agoraphobia) 64%. Both cluster A (anxious personality) and cluster B (e.g., borderline and histrionic) personality disorders were highly prevalent. These data suggest that the "atypicality" of depression is favored by affective temperamental dysregulation and anxiety comorbidity, clinically manifesting in a mood disorder subtype that is preponderantly in the realm of bipolar II. In the present sample, only 28% were strictly unipolar and characterized by avoidant and social phobic features, without histrionic traits. PMID:9515190

  4. Primary Follicular Lymphoma of the Duodenum with Erosions as Atypical Macroscopic Features

    PubMed Central

    Takeuchi, Keiko; Iwamuro, Masaya; Imagawa, Atsushi; Kubota, Yoshitsugu; Miyatani, Katsuya; Takata, Katsuyoshi; Okada, Hiroyuki

    2012-01-01

    A 52-year-old Japanese woman who was eventually diagnosed with primary follicular lymphoma of the duodenum showed atypical endoscopic features, namely, erosions with peripheral whitish edematous mucosa. Initial biopsy specimens taken from the erosions revealed insufficient numbers of lymphoma cells for histological diagnosis. Subsequent biopsy specimens from the peripheral mucosa containing the whitish enlarged villi showed infiltration of the lymphoma cells forming lymphoid follicles, which led us to the appropriate diagnosis. This case indicates that endoscopists should take biopsy samples from the peripheral mucosa with whitish enlarged villi rather than erosions in the rare instances that erosions appear as the main macroscopic feature of intestinal follicular lymphoma. PMID:22690224

  5. Featured Image: Spitzer Galaxies

    NASA Astrophysics Data System (ADS)

    Kohler, Susanna

    2015-11-01

    These three galaxies (click for a full view!) were imaged as a part of the Spitzer Survey of Stellar Structure in Galaxies (S4G), a recent survey of 2352 nearby galaxies with deep imaging at 3.6 and 4.5 m. The bottom panels show false-color near-UV and far-UV images previously obtained with GALEX. The top panels show the new images obtained with Spitzer as part of S4G. The three galaxies shown here represent three types of galaxies that have a high concentration of mass in their centers, yet still have a high specific star-formation rate (the star formation rate per unit stellar mass):Barred galaxies with a prominent ring around their nucleus, like NGC 7552Interacting systems, like NGC 2782Galaxies with compact bulges and smooth extended disks, like NGC 3642To learn why this is the case, and to see more results from S4G, see the original paper below.CitationJuan Carlos Muoz-Mateos et al 2015 ApJS 219 3. doi:10.1088/0067-0049/219/1/3

  6. ZFP36-FOSB Fusion Defines a Subset of Epithelioid Hemangioma with Atypical Features

    PubMed Central

    Antonescu, Cristina R; Chen, Hsiao-Wei; Zhang, Lei; Sung, Yun-Shao; Panicek, David; Agaram, Narasimhan P; Dickson, Brendan C; Krausz, Thomas; Fletcher, Christopher D

    2014-01-01

    Epithelioid hemangioma (EH) is a benign neoplasm with distinctive vasoformative features, which occasionally shows increased cellularity, cytologic atypia, and/or loco-regional aggressive growth, resulting in challenging differential diagnosis from malignant vascular neoplasms. Based on two intra-osseous EH index cases with worrisome histologic features, such as the presence of necrosis, RNA sequencing was applied for possible fusion gene discovery and potential subclassification of a novel atypical EH subset. A ZFP36-FOSB fusion was detected in one case, while a WWTR1-FOSB chimeric transcript in the other, both were further validated by FISH and RT-PCR. These abnormalities were then screened by FISH in 44 EH from different locations with 7 additional EH revealing FOSB gene rearrangements, all except one being fused to ZFP36. Interestingly, 4/6 penile EH studied showed FOSB abnormalities. Although certain atypical histologic features were observed in the FOSB-rearranged EH, including solid growth, increased cellularity, mild to moderate nuclear pleomorphism, and necrosis in 3/9 cases, no overt sarcomatous areas were discerned to objectively separate the lesions from the fusion-negative EH. No patient has developed recurrence to date, but the follow-up was relatively limited and short to draw definitive conclusions regarding behavior. Although FOSB-rearranged EH do not show significant morphologic overlap with SERPINE1-FOSB fusion-positive pseudomyogenic hemangioendothelioma, FOSB oncogenic activation is emerging as an important event in these benign and intermediate groups of vascular tumors. PMID:25043949

  7. Atypicality of Atypical Antipsychotics

    PubMed Central

    Farah, Andrew

    2005-01-01

    Objective: To review the current definition of atypicality, discuss the unique features of each atypical antipsychotic, and determine whether the available drugs in this class really meet the classical definition of atypicality. Data Sources: A PubMed search was conducted to identify literature on the subject of this review, supported by additional articles based on the author's clinical knowledge and experience. Study Selection and Data Extraction: Relevant references were extracted and summarized in order to meet the objective of the article. Data Synthesis: Atypical antipsychotics are considered a major advance over conventional antipsychotics, primarily because they offer effective treatment alternatives that are relatively free of extrapyramidal symptoms. In fact, the term atypicality was originally used to describe antipsychotic agents with a minimal risk of causing extrapyramidal symptoms. However, over the years the definition has been modified such that there is currently no consensus on a true definition of atypicality for these agents. Each of the atypical antipsychotics (clozapine, risperidone, olanzapine, quetiapine, ziprasidone, and aripiprazole) commercially available in the United States is unique in terms of its pharmacologic profile, differing with respect to receptor-binding affinity, mechanism of action, and adverse events. Of the available atypical antipsychotics, clozapine and quetiapine have shown the lowest propensity to cause extrapyramidal symptoms. Although the risk of extra-pyramidal symptoms is lower with risperidone and olanzapine than with conventional antipsychotics, risk increases with dose escalation. Data for ziprasidone indicate that the risk of extrapyramidal symptoms may be similar to that of risperidone and olanzapine. There is a concern of akathisia with aripiprazole; however, more experience with this agent is needed before definitive conclusions are made. Conclusion: If the definition of “atypical” antipsychotic is

  8. Atypical patterns in portable monitoring for sleep apnoea: features of nocturnal epilepsy?

    PubMed

    Parrino, Liborio; Milioli, Giulia; Grassi, Andrea; De Paolis, Fernando; Riccardi, Silvia; Colizzi, Elena; Bosi, Marcello; Terzano, Mario Giovanni

    2013-02-01

    Atypical cardiorespiratory patterns can be found during routine clinical use of portable monitoring for diagnosis of sleep-disordered breathing (SDB). Over 1,000 consecutive portable recordings were analysed to study the potential ictal nature of stereotyped cardiorespiratory and motor patterns. Snoring, airflow, thoracic effort, pulse rate, body position, oxygen saturation and activity of the anterior tibialis muscles were quantified. Recordings showing stereotyped polygraphic patterns recurring throughout the night, but without the features of sleep apnoea (apnoea/hypopnoea index <5 events·h(-1)), were selected for investigation. Once included in the study, patients underwent attended nocturnal video polysomnography. A total of 15 recordings showing repeated polygraphic patterns characterised by a sequence of microphone activation, respiratory activity atypical for sleep and wakefulness, heart rate acceleration and limb movements, followed by body position change, were selected for investigation. Once included in the study, patients underwent attended nocturnal video polysomnography that showed frontal epileptic discharges triggering periodic electroencephalographic arousals, autonomic activation and stereotyped motor patterns. A diagnosis of nocturnal frontal lobe epilepsy (NFLE) was established for all patients. NFLE should be taken into consideration in patients with stereotyped and recurrent behavioural features during portable monitoring carried out for diagnosis of SDB. PMID:22700842

  9. The typical and atypical MR imaging findings of central neurocytomas: Report on eighteen cases and review of the literature.

    PubMed

    Ma, Zhanlong; Yan, Hailang; Shi, Haibin; Li, Yan; Song, Jiacheng; Huang, Junwen; Hong, Xiongning

    2016-07-01

    There were few studies have documented the MRI features of typical and atypical CNCs for diagnosis and therapeutic modalities. Here, 18 histopathologically confirmed cases of intracranial CNCs (8 men and 10 women with a mean age of 28.3 years, range 10-64 years) were retrospectively analyzed. The histopathological and immunohistochemical features were also assessed. On MR imaging, the 14 typical cases of CNCs showed relatively round, lobulated tumor masses in the body of the right lateral ventricle (5 cases), left lateral ventricle (4 cases), third ventricles (2 cases), and midline (3 cases). These typical CNCs masses contained clusters of cysts of varying sizes and "soap bubble" appearance on T2WI; they showed mild to moderate heterogeneously enhancement on T1WI. The 4 atypical cases of CNCs showed as strongly contrast enhancement of the tumors with the attachment or infiltrate of the wall of the ventricle than the typical benign cases. These atypical CNCs were in the right lateral ventricle (2 cases), left lateral ventricle (1 case), and third ventricle (1 case). Microscopically, the typical CNCs were well-differentiated tumors with benign histological features. The typical and atypical CNCs were composed of uniform, small to medium-sized cells with rounded nuclei and scant cytoplasm. Immunohistochemically, the typical CNCs were strong in Syn immunopositive (14/14) and neuron-specific enolase (12/14). The atypical CNC tumor cells showed malignant behavior and more positive expression of Ki67 than the benign cases. Surgery is the first choice of treatment, and radiotherapy may be beneficial to postoperative patients. PMID:27132079

  10. Image segmentation using random features

    NASA Astrophysics Data System (ADS)

    Bull, Geoff; Gao, Junbin; Antolovich, Michael

    2014-01-01

    This paper presents a novel algorithm for selecting random features via compressed sensing to improve the performance of Normalized Cuts in image segmentation. Normalized Cuts is a clustering algorithm that has been widely applied to segmenting images, using features such as brightness, intervening contours and Gabor filter responses. Some drawbacks of Normalized Cuts are that computation times and memory usage can be excessive, and the obtained segmentations are often poor. This paper addresses the need to improve the processing time of Normalized Cuts while improving the segmentations. A significant proportion of the time in calculating Normalized Cuts is spent computing an affinity matrix. A new algorithm has been developed that selects random features using compressed sensing techniques to reduce the computation needed for the affinity matrix. The new algorithm, when compared to the standard implementation of Normalized Cuts for segmenting images from the BSDS500, produces better segmentations in significantly less time.

  11. Diagnostic Value of I-131 NP-59 SPECT/CT Scintigraphy in Patients with Subclinical or Atypical Features of Primary Aldosteronism

    PubMed Central

    Chen, Yi-Chun; Su, Yu-Chieh; Wei, Chang-Kuo; Chiu, Jainn-Shiun; Tseng, Chih-En; Chen, Shao-Jer; Wang, Yuh-Feng

    2011-01-01

    Accumulating evidence has shown the adverse effect of long-term hyperaldosteronism on cardiovascular morbidity that is independent of blood pressure. However, the diagnosis of primary aldosteronism (PA) remains a challenge for patients who present with subtle or atypical features or have chronic kidney disease (CKD). SPECT/CT has proven valuable in the diagnosis of a number of conditions. The aim of this study was to determine the usefulness of I-131 NP-59 SPECT/CT in patients with atypical presentations of PA and in those with CKD. The records of 15 patients with PA were retrospectively analyzed. NP-59 SPECT/CT was able to identify adrenal lesion(s) in CKD patients with suspected PA. Patients using NP-59 SPECT/CT imaging, compared with those not performing this procedure, significantly featured nearly normal serum potassium levels, normal aldosterone-renin ratio, and smaller adrenal size on CT and pathological examination and tended to feature stage 1 hypertension and non-suppressed plasma renin activity. These findings show that noninvasive NP-59 SPECT/CT is a useful tool for diagnosis in patients with subclinical or atypical features of PA and those with CKD. PMID:21541242

  12. Depressed older patients with the atypical features of interpersonal rejection sensitivity and reversed-vegetative symptoms are similar to younger atypical patients

    PubMed Central

    Sachs-Ericsson, Natalie; Selby, Edward; Corsentino, Elizabeth; Collins, Nicole; Sawyer, Kathryn; Hames, Jennifer; Arce, Darleine; Joiner, Thomas; Steffens, David C.

    2012-01-01

    Objectives The atypical depression (AD) subtype has rarely been examined in older patients. However, younger AD patients have been characterized as having more severe and chronic symptoms of depression compared with non-AD patients. Design Secondary data analysis using ANOVAs and Growth Curve Modeling. Setting Clinical Research Center for the Study of Depression in Later Life. Participants Depressed older patients (N=248) followed over 2 years. Method In a longitudinal study, we examined depression severity and chronicity in patients with major depression with some features of atypical depression, specifically rejection sensitivity and reversed-vegetative symptoms (e.g., hyperphagia, hypersomnia), or leaden paralysis, and compared them to non-AD patients. The Diagnostic Interview Schedule (DIS) was used to assess depressive symptoms and history. Depression severity and chronicity were assessed every three months using the Montgomery Asberg Depression Rating Scale. Results The AD symptom group reported more DIS depressive symptoms, more thoughts about wanting to die, earlier age of onset, poorer social support and double the number of lifetime episodes than non-AD patients. Growth curve analyses revealed that, compared with non-AD patients, the AD symptom group had more residual symptoms of depression during the first year of follow-up, but not during the second year. Conclusion Characteristics of older patients with features of AD are similar to younger patients. Assessment of atypical symptoms, in particular rejection sensitivity and reversed-vegetative symptoms is essential, and should be considered in treatment plans. PMID:21997599

  13. Gastrointestinal stromal tumours (GISTs) with a thousand faces: atypical manifestations and causes of misdiagnosis on imaging.

    PubMed

    Kim, S W; Kim, H C; Yang, D M; Won, K Y

    2016-02-01

    Gastrointestinal stromal tumours (GISTs) can lead to emergency situations, such as gastrointestinal bleeding, intestinal obstruction, and tumoural rupture with haemoperitoneum or peritonitis. In addition, if a GIST grows exophytically to a large size, it is often misdiagnosed as a tumour arising from adjacent organs. Sometimes, the atypical appearance of GISTs on imaging causes diagnostic confusion. In this article, we illustrate a variety of GISTs with atypical presentations and also discuss the important diagnostic clues for differentiating GISTs from other lesions. PMID:26646370

  14. Detection of Variable Gaseous Absorption Features in the Debris Disks Around Young A-type Stars

    NASA Astrophysics Data System (ADS)

    Montgomery, Sharon L.; Welsh, Barry Y.

    2012-10-01

    We present medium resolution (R = 60,000) absorption measurements of the interstellar Ca II K line observed towards five nearby A-type stars (49 Ceti, 5 Vul, ι Cyg, 2 And, and HD 223884) suspected of possessing circumstellar gas debris disks. The stars were observed on a nightly basis during a six night observing run on the 2.1-meter Otto Struve telescope at the McDonald Observatory, Texas. We have detected nightly changes in the absorption strength of the Ca II K line observed near the stellar radial velocity in three of the stars (49 Ceti, i Cyg and HD 223884). Such changes in absorption suggest the presence of a circumstellar (atomic) gas disk around these stars. In addition to the absorption changes in the main Ca II K line profile, we have also observed weak transient absorption features that randomly appear at redshifted velocities in the spectra of 49 Ceti, 5 Vul, and 2 And. These absorption features are most probably associated with the presence of falling evaporated bodies (exo-comets) that liberate evaporating gas on their approach to the central star. This now brings the total number of systems in which exocomet activity has been observed at Ca II or Na I wavelengths on a nightly basis to seven (β Pic, HR 10, HD 85905, β Car, 49 Ceti, 5 Vul, and 2 And), with 2 And exhibiting weaker and less frequent changes. All of the disk systems presently known to exhibit either type of short-term variability in Ca II K line absorption are rapidly rotating A-type stars (V sin i > 120 km s-1). Most exhibit mid-IR excesses, and many of them are very young (< 20 Myr), thus supporting the argument that many of them are transitional objects between Herbig Ae and "Vega-like" A-type stars with more tenuous circumstellar disks. No mid-IR excess (due to the presence of a dust disk) has yet been detected around either 2 And or HD 223884, both of which have been classified as λ Boötis-type stars. This may indicate that the observed changes in gas absorption for these two

  15. Characterization of the Autophagy Marker Protein Atg8 Reveals Atypical Features of Autophagy in Plasmodium falciparum

    PubMed Central

    Allanki, Aparna Devi; Sijwali, Puran Singh

    2014-01-01

    Conventional autophagy is a lysosome-dependent degradation process that has crucial homeostatic and regulatory functions in eukaryotic organisms. As malaria parasites must dispose a number of self and host cellular contents, we investigated if autophagy in malaria parasites is similar to the conventional autophagy. Genome wide analysis revealed a partial autophagy repertoire in Plasmodium, as homologs for only 15 of the 33 yeast autophagy proteins could be identified, including the autophagy marker Atg8. To gain insights into autophagy in malaria parasites, we investigated Plasmodium falciparum Atg8 (PfAtg8) employing techniques and conditions that are routinely used to study autophagy. Atg8 was similarly expressed and showed punctate localization throughout the parasite in both asexual and sexual stages; it was exclusively found in the pellet fraction as an integral membrane protein, which is in contrast to the yeast or mammalian Atg8 that is distributed among cytosolic and membrane fractions, and suggests for a constitutive autophagy. Starvation, the best known autophagy inducer, decreased PfAtg8 level by almost 3-fold compared to the normally growing parasites. Neither the Atg8-associated puncta nor the Atg8 expression level was significantly altered by treatment of parasites with routinely used autophagy inhibitors (cysteine (E64) and aspartic (pepstatin) protease inhibitors, the kinase inhibitor 3-methyladenine, and the lysosomotropic agent chloroquine), indicating an atypical feature of autophagy. Furthermore, prolonged inhibition of the major food vacuole protease activity by E64 and pepstatin did not cause accumulation of the Atg8-associated puncta in the food vacuole, suggesting that autophagy is primarily not meant for degradative function in malaria parasites. Atg8 showed partial colocalization with the apicoplast; doxycycline treatment, which disrupts apicoplast, did not affect Atg8 localization, suggesting a role, but not exclusive, in apicoplast

  16. Efficient image representations and features

    NASA Astrophysics Data System (ADS)

    Dorr, Michael; Vig, Eleonora; Barth, Erhardt

    2013-03-01

    Interdisciplinary research in human vision and electronic imaging has greatly contributed to the current state of the art in imaging technologies. Image compression and image quality are prominent examples and the progress made in these areas relies on a better understanding of what natural images are and how they are perceived by the human visual system. A key research question has been: given the (statistical) properties of natural images, what are the most efficient and perceptually relevant image representations, what are the most prominent and descriptive features of images and videos? We give an overview of how these topics have evolved over the 25 years of HVEI conferences and how they have influenced the current state of the art. There are a number of striking parallels between human vision and electronic imaging. The retina does lateral inhibition, one of the early coders was using a Laplacian pyramid; primary visual cortical areas have orientation- and frequency-selective neurons, the current JPEG standard defines similar wavelet transforms; the brain uses a sparse code, engineers are currently excited about sparse coding and compressed sensing. Some of this has indeed happened at the HVEI conferences and we would like to distill that.

  17. Textural features for image classification

    NASA Technical Reports Server (NTRS)

    Haralick, R. M.; Dinstein, I.; Shanmugam, K.

    1973-01-01

    Description of some easily computable textural features based on gray-tone spatial dependances, and illustration of their application in category-identification tasks of three different kinds of image data - namely, photomicrographs of five kinds of sandstones, 1:20,000 panchromatic aerial photographs of eight land-use categories, and ERTS multispectral imagery containing several land-use categories. Two kinds of decision rules are used - one for which the decision regions are convex polyhedra (a piecewise-linear decision rule), and one for which the decision regions are rectangular parallelpipeds (a min-max decision rule). In each experiment the data set was divided into two parts, a training set and a test set. Test set identification accuracy is 89% for the photomicrographs, 82% for the aerial photographic imagery, and 83% for the satellite imagery. These results indicate that the easily computable textural features probably have a general applicability for a wide variety of image-classification applications.

  18. Novel Mutation of the GNE Gene Presenting Atypical Mild Clinical Feature: A Korean Case Report.

    PubMed

    Choi, Young-Ah; Park, Sung-Hye; Yi, Youbin; Kim, Keewon

    2015-06-01

    Glucosamine (UDP-N-acetyl)-2-epimerase/N-acetylmannosamine kinase (GNE) myopathy is caused by mutations in GNE, a key enzyme in sialic acid biosynthesis. Here, we reported a case of GNE that presented with atypical mild clinical feature and slow progression. A 48-year-old female had a complaint of left foot drop since the age of 46 years. Electromyography (EMG) and muscle biopsy from left tibialis anterior muscle were compatible with myopathy. Genetic analysis led to the identification of c.1714G>C/c.527A>T compound heterozygous mutation, which is the second most frequent mutation in Japan as far as we know. Previous research has revealed that c.1714G>C/c.527A>T compound heterozygous mutation is a mild mutation as the onset of the disease is much later than the usual age of onset of GNE myopathy and the clinical course is slowly progressive. This was the first case report in Korea of the clinicopathological characteristics of GNE myopathy with GNE (c.1714G>C/c.527A>T compound heterozygous) mutation. PMID:26161358

  19. Extramedullary haematopoiesis: radiological imaging features.

    PubMed

    Roberts, A S; Shetty, A S; Mellnick, V M; Pickhardt, P J; Bhalla, S; Menias, C O

    2016-09-01

    Extramedullary haematopoiesis (EMH) is defined as the production of blood cells outside of the bone marrow, which occurs when there is inadequate production of blood cells. The most common causes of EMH are myelofibrosis, diffuse osseous metastatic disease replacing the bone marrow, leukaemia, sickle cell disease, and thalassemia. The purpose of this article is to review the common and uncommon imaging appearances of EMH by anatomical compartment. In the thorax, EMH most commonly presents as paravertebral fat-containing masses, and typically does not present a diagnostic dilemma; however, EMH in the abdomen most commonly manifests as hepatosplenomegaly with or without focal soft-tissue masses in the liver, spleen, perirenal space, and in the peritoneum. Hepatosplenomegaly, a non-specific feature, most often occurs without an associated focal mass, which makes suggestion of EMH difficult. EMH manifesting as visceral soft-tissue masses often requires biopsy as the differential diagnosis can include lymphoma, metastatic disease, and sarcoma. Many of these soft-tissue masses do not contain adipose elements, making the diagnosis of EMH difficult. Clinical history is crucial, as EMH would likely not otherwise be in the differential in patients with non-specific abdominal masses. Careful biopsy planning is necessary when EMH is a diagnostic consideration, given the propensity for haemorrhage. Understanding the typical imaging appearances of EMH based on its site of manifestation can help the radiologist when encountered with a finding that is diagnostic for EMH, and can help the radiologist suggest the need and plan appropriately for image-guided biopsy. PMID:27377325

  20. The Utility of Gadoxetic Acid-Enhanced MR Imaging to Characterize Atypical Cirrhotic Nodules Detected on Dynamic CT Images

    PubMed Central

    Chou, Chen-Te; Wu, Wen-Pei; Chen, Chia-Bang; Su, Wei-Wen; Chen, Ran-Chou; Chen, Yao-Li

    2014-01-01

    Purpose To evaluate whether gadoxetic acid (Gd-EOB-DTPA)-enhanced MR images of tumors taken during the hepatocyte-specific phase can aid in the differentiation between hepatocellular carcinoma (HCC) and dysplastic nodules (DNs) in patients with atypical cirrhotic nodules detected on dynamic CT images. Materials and Methods Seventy-one patients with 112 nodules showing atypical dynamic enhancement on CT images underwent gadoxetic acid-enhanced MR imaging (MRI) studies. Using a reference standard, we determined that 33 of the nodules were DNs and that 79 were true HCCs. Tumor size, signal intensity on precontrast T1-weighted images (T1WI) and T2WI, and the pattern of dynamic enhancement on MR images taken in the hepatocyte-phase were determined. Results There were significant differences in tumor size, hyperintensity on T2WI, hypointensity on T1WI, typical HCC enhancement pattern on dynamic MR images, or hypointensity on hepatocyte-phase images between DNs and HCC. The sensitivity and specificity were 60.8% and 87.9% for T2WI, 38.0% and 87.9% for T1WI, 17.7% and 100% for dynamic MR imaging, 83.5% and 84.9% for hepatocyte-phase imaging, and 60.8% and 87.9% for tumor size (threshold of 1.7 cm). Conclusion Gd-EOB-DTPA-enhanced hepatocyte-phase imaging is recommended for patients at high risk of HCC who present with atypical lesions on dynamic CT images. PMID:25310817

  1. Atypical presentation of Lemierre syndrome: role of imaging

    PubMed Central

    Kumar, Manoj; Singh, Ragini; Sawlani, Kamal Kumar; Kumar, Santosh

    2013-01-01

    A 51-year-old male patient presented with breathlessness for 10 days. Chest radiograph revealed bilateral moderate pleural effusion. Ultrasound-guided diagnostic pleural aspirate revealed sterile transudative fluid. CT thorax revealed bilateral moderate pleural effusion with partial collapse of both lower lobes and thrombus in right brachiocephalic vein. Two-dimensional-echo revealed circumferential pericardial effusion with mild pericardial thickening and moderate tricuspid regurgitation. Cardiolipin antibodies were within normal limits. d-Dimer assay and C reactive protein were markedly raised. During the period of investigations, the patient had developed mild swelling and pain in right upper limb for which colour Doppler ultrasonography of his right upper limb and neck regions were done. Thrombi in right internal jugular, subclavian and brachiocephalic veins were noted. CT angiography, CT abdomen and chest confirmed the above findings. However, extent of the thrombus and lung lesions was better delineated by CT angiography. We have highlighted the pathognomonic imaging findings of Lemierre syndrome. PMID:23345481

  2. Image fusion using sparse overcomplete feature dictionaries

    SciTech Connect

    Brumby, Steven P.; Bettencourt, Luis; Kenyon, Garrett T.; Chartrand, Rick; Wohlberg, Brendt

    2015-10-06

    Approaches for deciding what individuals in a population of visual system "neurons" are looking for using sparse overcomplete feature dictionaries are provided. A sparse overcomplete feature dictionary may be learned for an image dataset and a local sparse representation of the image dataset may be built using the learned feature dictionary. A local maximum pooling operation may be applied on the local sparse representation to produce a translation-tolerant representation of the image dataset. An object may then be classified and/or clustered within the translation-tolerant representation of the image dataset using a supervised classification algorithm and/or an unsupervised clustering algorithm.

  3. Atypical hemispheric asymmetries for the processing of phonological features in children with rolandic epilepsy.

    PubMed

    Bedoin, Nathalie; Ferragne, Emmanuel; Lopez, Céline; Herbillon, Vania; De Bellescize, J; des Portes, Vincent

    2011-05-01

    We assessed language lateralization in 177 healthy 4- to 11-year-old children and adults and atypical asymmetries associated with unilateral epileptic foci in 18 children with benign epilepsy with centrotemporal spikes (BECTS). Dichotic listening results revealed two indices of immature functional asymmetry when the focus was left-sided (BECTS-L). First, children with BECTS-L did not show left hemisphere dominance for the processing of place of articulation, which was recorded in children with BECTS-R and control children. On the contrary, healthy children exhibited a gradual increase in left hemisphere dominance for place processing during childhood, which is consistent with the shift from global to finer-grained acoustic analysis predicted by the Developmental Weighting Shift model. Second, children with BECTS-L showed atypical left hemisphere involvement in the processing of the voiced value (+V), associated with a long acoustic event in French stop consonants, whereas right hemisphere dominance increased with age for +V processing in healthy children. BECTS-L, therefore, interferes with the development of left hemisphere dominance for specific phonological mechanisms. PMID:21470917

  4. Featured Image: Solar Prominence Eruptions

    NASA Astrophysics Data System (ADS)

    Kohler, Susanna

    2016-02-01

    In these images from the Solar Dynamics Observatorys AIA instrument (click for the full resolution!), two solar prominence eruptions (one from June 2011 and one from August 2012) are shown in pre- and post-eruption states. The images at the top are taken in the Fe XII 193 bandpass and the images at the bottom are taken in the He II 304 bandpass. When a team of scientists searched through seven years of solar images taken by the STEREO (Solar Terrestrial Relations Observatory) spacecraft, these two eruptions were found to extend all the way out to a distance of 1 AU. They were the only two examples of clear, bright, and compact prominence eruptions found to do so. The scientists, led by Brian Wood (Naval Research Laboratory), used these observations to reconstruct the motion of the eruption and model how prominences expand as they travel away from the Sun. Theimage to the rightshowsa STEREO observation compared to the teams 3D model of theprominences shape and expansion. To learn more about theresults from this study, check out the paper below.CitationBrian E. Wood et al 2016 ApJ 816 67. doi:10.3847/0004-637X/816/2/67

  5. Humane images: visual rhetoric in depictions of atypical genital anatomy and sex differentiation.

    PubMed

    Wall, Shelley

    2010-12-01

    Visual images are widely used in medical and patient education to enhance spoken or written explanations. This paper considers the role of such illustrations in shaping conceptions of the body; specifically, it addresses depictions of variant sexual anatomy and their part in the discursive production of intersex bodies. Visual language--even didactic, 'factual' visual language--carries latent as well as manifest content, and influences self-perceptions and social attitudes. In the case of illustrations about atypical sex development, where the need for non-stigmatising communication is crucial, it is especially important to consider the implicit messages conveyed by imagery and compositional strategies. PMID:21393287

  6. Retinal image quality assessment using generic features

    NASA Astrophysics Data System (ADS)

    Fasih, Mahnaz; Langlois, J. M. Pierre; Ben Tahar, Houssem; Cheriet, Farida

    2014-03-01

    Retinal image quality assessment is an important step in automated eye disease diagnosis. Diagnosis accuracy is highly dependent on the quality of retinal images, because poor image quality might prevent the observation of significant eye features and disease manifestations. A robust algorithm is therefore required in order to evaluate the quality of images in a large database. We developed an algorithm for retinal image quality assessment based on generic features that is independent from segmentation methods. It exploits the local sharpness and texture features by applying the cumulative probability of blur detection metric and run-length encoding algorithm, respectively. The quality features are combined to evaluate the image's suitability for diagnosis purposes. Based on the recommendations of medical experts and our experience, we compared a global and a local approach. A support vector machine with radial basis functions was used as a nonlinear classifier in order to classify images to gradable and ungradable groups. We applied our methodology to 65 images of size 2592×1944 pixels that had been graded by a medical expert. The expert evaluated 38 images as gradable and 27 as ungradable. The results indicate very good agreement between the proposed algorithm's predictions and the medical expert's judgment: the sensitivity and specificity for the local approach are respectively 92% and 94%. The algorithm demonstrates sufficient robustness to identify relevant images for automated diagnosis.

  7. Adenoma or atypical hepatic focal nodular hyperplasia: role of preoperative imaging and laparoscopic treatment.

    PubMed

    Di Carlo, Isidoro; Pulvirenti, Elia; Toro, Adriana; Priolo, Gian Domenico

    2010-06-01

    Differentiation of focal nodular hyperplasia (FNH) and other hypervascular liver lesions, such as hepatocellular adenoma (HCA), is important because of the drastically different therapeutic approach. However, FNH can be well distinguished only if it shows a typical aspect; alternatively, in the case of atypical FNH, imaging findings are not specific enough to provide a secure diagnosis and histologic verification of the lesion is required. In addition, HCA cannot be identified conclusively by any current available imaging technique and it can be at best suspected strongly, and this suspicion may lead to liver resection. Herein we report a case of a patient with an unusual FNH nodule presenting at ultrasonographic scanning as an isoechoic mass arising from hepatic segment 4b; the diagnostic indecision between FNH and HCA was not definitively solved even after computed tomography scan and magnetic resonance imaging and the patient was scheduled for a laparoscopic resection. The pathologic examination diagnosed an atypical FNH nodule. The clinical doubt between FNH and HCA remains a problem affecting the clinicians, and more effort should be made in the direction of a better preoperative differentiation of such different conditions. Surgical resection should not be considered as the failure of the preoperative diagnostic attempt, but as the mainstay for a definitive and sure diagnosis. PMID:20551788

  8. Quantitative imaging features: extension of the oncology medical image database

    NASA Astrophysics Data System (ADS)

    Patel, M. N.; Looney, P. T.; Young, K. C.; Halling-Brown, M. D.

    2015-03-01

    Radiological imaging is fundamental within the healthcare industry and has become routinely adopted for diagnosis, disease monitoring and treatment planning. With the advent of digital imaging modalities and the rapid growth in both diagnostic and therapeutic imaging, the ability to be able to harness this large influx of data is of paramount importance. The Oncology Medical Image Database (OMI-DB) was created to provide a centralized, fully annotated dataset for research. The database contains both processed and unprocessed images, associated data, and annotations and where applicable expert determined ground truths describing features of interest. Medical imaging provides the ability to detect and localize many changes that are important to determine whether a disease is present or a therapy is effective by depicting alterations in anatomic, physiologic, biochemical or molecular processes. Quantitative imaging features are sensitive, specific, accurate and reproducible imaging measures of these changes. Here, we describe an extension to the OMI-DB whereby a range of imaging features and descriptors are pre-calculated using a high throughput approach. The ability to calculate multiple imaging features and data from the acquired images would be valuable and facilitate further research applications investigating detection, prognosis, and classification. The resultant data store contains more than 10 million quantitative features as well as features derived from CAD predictions. Theses data can be used to build predictive models to aid image classification, treatment response assessment as well as to identify prognostic imaging biomarkers.

  9. Featured Image: Modeling Supernova Remnants

    NASA Astrophysics Data System (ADS)

    Kohler, Susanna

    2016-05-01

    This image shows a computer simulation of the hydrodynamics within a supernova remnant. The mixing between the outer layers (where color represents the log of density) is caused by turbulence from the Rayleigh-Taylor instability, an effect that arises when the expanding core gas of the supernova is accelerated into denser shell gas. The past standard for supernova-evolution simulations was to perform them in one dimension and then, in post-processing, manually smooth out regions that undergo Rayleigh-Taylor turbulence (an intrinsically multidimensional effect). But in a recent study, Paul Duffell (University of California, Berkeley) has explored how a 1D model could be used to reproduce the multidimensional dynamics that occur in turbulence from this instability. For more information, check out the paper below!CitationPaul C. Duffell 2016 ApJ 821 76. doi:10.3847/0004-637X/821/2/76

  10. Automatic Extraction of Planetary Image Features

    NASA Technical Reports Server (NTRS)

    Troglio, G.; LeMoigne, J.; Moser, G.; Serpico, S. B.; Benediktsson, J. A.

    2009-01-01

    With the launch of several Lunar missions such as the Lunar Reconnaissance Orbiter (LRO) and Chandrayaan-1, a large amount of Lunar images will be acquired and will need to be analyzed. Although many automatic feature extraction methods have been proposed and utilized for Earth remote sensing images, these methods are not always applicable to Lunar data that often present low contrast and uneven illumination characteristics. In this paper, we propose a new method for the extraction of Lunar features (that can be generalized to other planetary images), based on the combination of several image processing techniques, a watershed segmentation and the generalized Hough Transform. This feature extraction has many applications, among which image registration.

  11. Automatic extraction of planetary image features

    NASA Technical Reports Server (NTRS)

    LeMoigne-Stewart, Jacqueline J. (Inventor); Troglio, Giulia (Inventor); Benediktsson, Jon A. (Inventor); Serpico, Sebastiano B. (Inventor); Moser, Gabriele (Inventor)

    2013-01-01

    A method for the extraction of Lunar data and/or planetary features is provided. The feature extraction method can include one or more image processing techniques, including, but not limited to, a watershed segmentation and/or the generalized Hough Transform. According to some embodiments, the feature extraction method can include extracting features, such as, small rocks. According to some embodiments, small rocks can be extracted by applying a watershed segmentation algorithm to the Canny gradient. According to some embodiments, applying a watershed segmentation algorithm to the Canny gradient can allow regions that appear as close contours in the gradient to be segmented.

  12. Hemorrhage detection in MRI brain images using images features

    NASA Astrophysics Data System (ADS)

    Moraru, Luminita; Moldovanu, Simona; Bibicu, Dorin; Stratulat (Visan), Mirela

    2013-11-01

    The abnormalities appear frequently on Magnetic Resonance Images (MRI) of brain in elderly patients presenting either stroke or cognitive impairment. Detection of brain hemorrhage lesions in MRI is an important but very time-consuming task. This research aims to develop a method to extract brain tissue features from T2-weighted MR images of the brain using a selection of the most valuable texture features in order to discriminate between normal and affected areas of the brain. Due to textural similarity between normal and affected areas in brain MR images these operation are very challenging. A trauma may cause microstructural changes, which are not necessarily perceptible by visual inspection, but they could be detected by using a texture analysis. The proposed analysis is developed in five steps: i) in the pre-processing step: the de-noising operation is performed using the Daubechies wavelets; ii) the original images were transformed in image features using the first order descriptors; iii) the regions of interest (ROIs) were cropped from images feature following up the axial symmetry properties with respect to the mid - sagittal plan; iv) the variation in the measurement of features was quantified using the two descriptors of the co-occurrence matrix, namely energy and homogeneity; v) finally, the meaningful of the image features is analyzed by using the t-test method. P-value has been applied to the pair of features in order to measure they efficacy.

  13. Automatic Feature Extraction from Planetary Images

    NASA Technical Reports Server (NTRS)

    Troglio, Giulia; Le Moigne, Jacqueline; Benediktsson, Jon A.; Moser, Gabriele; Serpico, Sebastiano B.

    2010-01-01

    With the launch of several planetary missions in the last decade, a large amount of planetary images has already been acquired and much more will be available for analysis in the coming years. The image data need to be analyzed, preferably by automatic processing techniques because of the huge amount of data. Although many automatic feature extraction methods have been proposed and utilized for Earth remote sensing images, these methods are not always applicable to planetary data that often present low contrast and uneven illumination characteristics. Different methods have already been presented for crater extraction from planetary images, but the detection of other types of planetary features has not been addressed yet. Here, we propose a new unsupervised method for the extraction of different features from the surface of the analyzed planet, based on the combination of several image processing techniques, including a watershed segmentation and the generalized Hough Transform. The method has many applications, among which image registration and can be applied to arbitrary planetary images.

  14. Wood Recognition Using Image Texture Features

    PubMed Central

    Wang, Hang-jun; Zhang, Guang-qun; Qi, Heng-nian

    2013-01-01

    Inspired by theories of higher local order autocorrelation (HLAC), this paper presents a simple, novel, yet very powerful approach for wood recognition. The method is suitable for wood database applications, which are of great importance in wood related industries and administrations. At the feature extraction stage, a set of features is extracted from Mask Matching Image (MMI). The MMI features preserve the mask matching information gathered from the HLAC methods. The texture information in the image can then be accurately extracted from the statistical and geometrical features. In particular, richer information and enhanced discriminative power is achieved through the length histogram, a new histogram that embodies the width and height histograms. The performance of the proposed approach is compared to the state-of-the-art HLAC approaches using the wood stereogram dataset ZAFU WS 24. By conducting extensive experiments on ZAFU WS 24, we show that our approach significantly improves the classification accuracy. PMID:24146821

  15. Extraction of edge feature in cardiovascular image

    NASA Astrophysics Data System (ADS)

    Lu, Jianrong; Chen, Dongqing; Yu, Daoyin; Liu, Xiaojun

    2001-09-01

    Extraction of edge feature and accurate measurement of vascular diameter in cardiovascular image are the bases for labeling the coronary hierarchy, 3D refined reconstruction of the coronary arterial tree and accurate fusion between the calculated 3D vascular trees and other views. In order to extract vessels from the image, the grayscale minimization of the circle template and differential edge detection are put forward. Edge pixels of the coronary artery are set according to maximization of the differential value. The edge lines are determined after the edge pixels are smoothed by B-Spline function. The assessment of feature extraction is demonstrated by the excellent performance in computer simulation and actual application.

  16. Onboard Image Registration from Invariant Features

    NASA Technical Reports Server (NTRS)

    Wang, Yi; Ng, Justin; Garay, Michael J.; Burl, Michael C

    2008-01-01

    This paper describes a feature-based image registration technique that is potentially well-suited for onboard deployment. The overall goal is to provide a fast, robust method for dynamically combining observations from multiple platforms into sensors webs that respond quickly to short-lived events and provide rich observations of objects that evolve in space and time. The approach, which has enjoyed considerable success in mainstream computer vision applications, uses invariant SIFT descriptors extracted at image interest points together with the RANSAC algorithm to robustly estimate transformation parameters that relate one image to another. Experimental results for two satellite image registration tasks are presented: (1) automatic registration of images from the MODIS instrument on Terra to the MODIS instrument on Aqua and (2) automatic stabilization of a multi-day sequence of GOES-West images collected during the October 2007 Southern California wildfires.

  17. Different mutations at V363 MAPT codon are associated with atypical clinical phenotypes and show unusual structural and functional features.

    PubMed

    Rossi, Giacomina; Bastone, Antonio; Piccoli, Elena; Morbin, Michela; Mazzoleni, Giulia; Fugnanesi, Valeria; Beeg, Marten; Del Favero, Elena; Cantù, Laura; Motta, Simona; Salsano, Ettore; Pareyson, Davide; Erbetta, Alessandra; Elia, Antonio Emanuele; Del Sorbo, Francesca; Silani, Vincenzo; Morelli, Claudia; Salmona, Mario; Tagliavini, Fabrizio

    2014-02-01

    Microtubule-associated protein tau gene (MAPT) is one of the major genes linked to frontotemporal lobar degeneration, a group of neurodegenerative diseases clinically, pathologically, and genetically heterogeneous. In particular, MAPT mutations give rise to the subgroup of tauopathies. The pathogenetic mechanisms underlying the MAPT mutations so far described are the decreased ability of tau protein to promote microtubule polymerization (missense mutations) or the altered ratio of tau isoforms (splicing mutations), both leading to accumulation of hyperphosphorylated filamentous tau protein. Following a genetic screening of patients affected by frontotemporal lobar degeneration, we identified 2 MAPT mutations, V363I and V363A, leading to atypical clinical phenotypes, such as posterior cortical atrophy. We investigated in vitro features of the recombinant mutated tau isoforms and revealed unusual functional and structural characteristics such as an increased ability to promote microtubule polymerization and a tendency to form oligomeric instead of filamentous aggregates. Thus, we disclosed a greater than expected complexity of abnormal features of mutated tau isoforms. Overall our findings suggest a high probability that these mutations are pathogenic. PMID:24018212

  18. Operational observations of atypical meteorological features using the WSR-88D

    SciTech Connect

    Tongue, J.S.; Lehenbauer, G.J.; Michael, P.A.; Miller, M.A.

    1996-09-01

    The Weather Surveillance Radar-1988 Doppler (WSR-88D) provides invaluable information on a variety of meteorological phenomena. The high sensitivity of the WSR-88D allows for the observation of phenomena that were not observable with previous WSR`s. Precipitation phase, land-sea breeze circulations, and clouds are examples of phenomena that are now observable by the WSR-88D. The detection of these features has an enormous impact on forecast operations.

  19. Recurrent Wernicke's Encephalopathy in a 16-Year-Old Girl with Atypical Clinical and Radiological Features

    PubMed Central

    Lamdhade, S.; Almulla, A.; Alroughani, R.

    2014-01-01

    Background. Wernicke's Encephalopathy (WE) is a clinical diagnosis with serious neurological consequences. Its occurrence is underestimated in nonalcoholics and is uncommon in adolescents. We aim to draw the attention to a rare case, which had additional clinical and radiological features. Case. A 16-year-old girl presented with three-week history of vomiting secondary to intestinal obstruction. She developed diplopia soon after hospitalization. Neurological evaluation revealed restriction of bilateral lateral recti with horizontal nystagmus, and bilateral limb dysmetria. Brain MRI was normal. She had prompt improvement to thiamine. Four months later, she presented with headache, bilateral severe deafness, and tinnitus. Clinically, she had severe sensorineural hearing loss, bilateral lateral recti paresis, and gait ataxia. CT head showed bilateral caudate nucleus hypodensities. MRI brain revealed gadolinium enhancement of mamillary bodies and vermis. She had significant improvement after IV thiamine. Headache completely resolved while the ocular movements, hearing, and tinnitus improved partially in 72 hours. Conclusions. Recurrent WE in adolescence is uncommon. Headache, tinnitus, and deafness are rare clinical features. Although MRI study shows typical features of WE, the presence of bilateral caudate nuclei hypodensities on CT scan is uncommon. Prompt treatment with thiamine is warranted in suspected cases to prevent permanent neurological sequelae. PMID:24790762

  20. Multimodality imaging features of hereditary multiple exostoses

    PubMed Central

    Fitzgerald, L; Campbell, N; Lyburn, I D; Munk, P L; Buckley, O; Torreggiani, W C

    2013-01-01

    Hereditary multiple exostoses (HME) or diaphyseal aclasis is an inherited disorder characterised by the formation of multiple osteochondromas, which are cartilage-capped osseous outgrowths, and the development of associated osseous deformities. Individuals with HME may be asymptomatic or develop clinical symptoms, which prompt imaging studies. Different modalities ranging from plain radiographs to cross-sectional and nuclear medicine imaging studies can be helpful in the diagnosis and detection of complications in HME, including chondrosarcomatous transformation. We review the role and imaging features of these different modalities in HME. PMID:24004486

  1. Role of the Wada test and functional magnetic resonance imaging in preoperative mapping of language and memory: two atypical cases.

    PubMed

    Połczyńska, Monika M; Benjamin, Christopher F A; Moseley, Brian D; Walshaw, Patricia; Eliashiv, Dawn; Vigil, Celia; Jones, Michael; Bookheimer, Susan Y

    2015-01-01

    The Wada test is an invasive procedure used to determine cerebral memory and language dominance as well as risk of cognitive deficits following neurosurgery. However, the potential risks of Wada testing have led some to consider foregoing Wada testing in candidates for resective epilepsy surgery with right hemispheric seizure onset. We present two atypical cases in which the Wada test showed unexpected memory and language lateralization. These cases underscore the importance of functional magnetic resonance in which imaging and Wada examination in right-handed individuals even when the lesion would not suggest atypical language representation. PMID:25372664

  2. Prenatal features of Pena-Shokeir sequence with atypical response to acoustic stimulation.

    PubMed

    Pittyanont, Sirida; Jatavan, Phudit; Suwansirikul, Songkiat; Tongsong, Theera

    2016-09-01

    A fetal sonographic screening examination performed at 23 weeks showed polyhydramnios, micrognathia, fixed postures of all long bones, but no movement and no breathing. The fetus showed fetal heart rate acceleration but no movement when acoustic stimulation was applied with artificial larynx. All these findings persisted on serial examinations. The neonate was stillborn at 37 weeks and a final diagnosis of Pena-Shokeir sequence was made. In addition to typical sonographic features of Pena-Shokeir sequence, fetal heart rate accelerations with no movement in response to acoustic stimulation suggests that peripheral myopathy may possibly play an important role in the pathogenesis of the disease. © 2016 Wiley Periodicals, Inc. J Clin Ultrasound 44:459-462, 2016. PMID:27312123

  3. Multimodal imaging of temporal processing in typical and atypical language development.

    PubMed

    Kovelman, Ioulia; Wagley, Neelima; Hay, Jessica S F; Ugolini, Margaret; Bowyer, Susan M; Lajiness-O'Neill, Renee; Brennan, Jonathan

    2015-03-01

    New approaches to understanding language and reading acquisition propose that the human brain's ability to synchronize its neural firing rate to syllable-length linguistic units may be important to children's ability to acquire human language. Yet, little evidence from brain imaging studies has been available to support this proposal. Here, we summarize three recent brain imaging (functional near-infrared spectroscopy (fNIRS), functional magnetic resonance imaging (fMRI), and magnetoencephalography (MEG)) studies from our laboratories with young English-speaking children (aged 6-12 years). In the first study (fNIRS), we used an auditory beat perception task to show that, in children, the left superior temporal gyrus (STG) responds preferentially to rhythmic beats at 1.5 Hz. In the second study (fMRI), we found correlations between children's amplitude rise-time sensitivity, phonological awareness, and brain activation in the left STG. In the third study (MEG), typically developing children outperformed children with autism spectrum disorder in extracting words from rhythmically rich foreign speech and displayed different brain activation during the learning phase. The overall findings suggest that the efficiency with which left temporal regions process slow temporal (rhythmic) information may be important for gains in language and reading proficiency. These findings carry implications for better understanding of the brain's mechanisms that support language and reading acquisition during both typical and atypical development. PMID:25773611

  4. A rare case of atypical skull base meningioma with perineural spread

    PubMed Central

    Walton, Henry; Morley, Simon; Alegre-Abarrategui, Javier

    2015-01-01

    Atypical meningioma is a rare cause of perineural tumour spread. In this report, we present the case of a 46-year-old female with an atypical meningioma of the skull base demonstrating perineural tumour spread. We describe the imaging features of this condition and its distinguishing features from other tumours exhibiting perineural spread. PMID:27200171

  5. Hyperspectral image feature extraction accelerated by GPU

    NASA Astrophysics Data System (ADS)

    Qu, HaiCheng; Zhang, Ye; Lin, Zhouhan; Chen, Hao

    2012-10-01

    PCA (principal components analysis) algorithm is the most basic method of dimension reduction for high-dimensional data1, which plays a significant role in hyperspectral data compression, decorrelation, denoising and feature extraction. With the development of imaging technology, the number of spectral bands in a hyperspectral image is getting larger and larger, and the data cube becomes bigger in these years. As a consequence, operation of dimension reduction is more and more time-consuming nowadays. Fortunately, GPU-based high-performance computing has opened up a novel approach for hyperspectral data processing6. This paper is concerning on the two main processes in hyperspectral image feature extraction: (1) calculation of transformation matrix; (2) transformation in spectrum dimension. These two processes belong to computationally intensive and data-intensive data processing respectively. Through the introduction of GPU parallel computing technology, an algorithm containing PCA transformation based on eigenvalue decomposition 8(EVD) and feature matching identification is implemented, which is aimed to explore the characteristics of the GPU parallel computing and the prospects of GPU application in hyperspectral image processing by analysing thread invoking and speedup of the algorithm. At last, the result of the experiment shows that the algorithm has reached a 12x speedup in total, in which some certain step reaches higher speedups up to 270 times.

  6. Imaging features of spinal tanycytic ependymoma.

    PubMed

    Tomek, Michal; Jayajothi, Anandapadmanabhan; Brandner, Sebastian; Jaunmuktane, Zane; Lee, Cheong Hung; Davagnanam, Indran

    2016-02-01

    Tanycytic ependymoma is an unusual morphological variant of WHO grade II ependymoma, typically arising from the cervical or thoracic spinal cord. Although the literature deals extensively with pathological features of this tumour entity, imaging features have not been well characterised. The purpose of this study was to review magnetic resonance imaging (MRI) features of spinal tanycytic ependymomas reported in the literature to date, exemplified by a case of a patient with tanycytic ependymoma of the conus medullaris presenting to our hospital. A Medline search of the English literature for all previously published cases of spinal tanycytic ependymoma was carried out and the reported MRI features reviewed. The tumours were found to be typically well-demarcated masses, predominantly showing isointensity on T1-weighted signal, and T2-weighted hyperintensity, with variable patterns of contrast enhancement. A cystic component was seen in half of the cases, and in a minority a mural nodule was present within the cyst wall. Associated syrinx formation was observed in one-third of the cases and haemorrhage was rare, which may be helpful pointers in differentiating the lesion from other ependymoma subtypes. In conclusion, MRI characteristics of spinal tanycytic ependymoma are variable and non-specific, and radiological diagnosis thus remains challenging, although certain predominant features are identified in this report. Knowledge of these is important in the diagnostic differentiation from other intramedullary and extramedullary spinal tumours in order to guide appropriate surgical management. PMID:26755489

  7. Multispectral image fusion based on fractal features

    NASA Astrophysics Data System (ADS)

    Tian, Jie; Chen, Jie; Zhang, Chunhua

    2004-01-01

    Imagery sensors have been one indispensable part of the detection and recognition systems. They are widely used to the field of surveillance, navigation, control and guide, et. However, different imagery sensors depend on diverse imaging mechanisms, and work within diverse range of spectrum. They also perform diverse functions and have diverse circumstance requires. So it is unpractical to accomplish the task of detection or recognition with a single imagery sensor under the conditions of different circumstances, different backgrounds and different targets. Fortunately, the multi-sensor image fusion technique emerged as important route to solve this problem. So image fusion has been one of the main technical routines used to detect and recognize objects from images. While, loss of information is unavoidable during fusion process, so it is always a very important content of image fusion how to preserve the useful information to the utmost. That is to say, it should be taken into account before designing the fusion schemes how to avoid the loss of useful information or how to preserve the features helpful to the detection. In consideration of these issues and the fact that most detection problems are actually to distinguish man-made objects from natural background, a fractal-based multi-spectral fusion algorithm has been proposed in this paper aiming at the recognition of battlefield targets in the complicated backgrounds. According to this algorithm, source images are firstly orthogonally decomposed according to wavelet transform theories, and then fractal-based detection is held to each decomposed image. At this step, natural background and man-made targets are distinguished by use of fractal models that can well imitate natural objects. Special fusion operators are employed during the fusion of area that contains man-made targets so that useful information could be preserved and features of targets could be extruded. The final fused image is reconstructed from the

  8. Feature-Linking Model for Image Enhancement.

    PubMed

    Zhan, Kun; Teng, Jicai; Shi, Jinhui; Li, Qiaoqiao; Wang, Mingying

    2016-06-01

    Inspired by gamma-band oscillations and other neurobiological discoveries, neural networks research shifts the emphasis toward temporal coding, which uses explicit times at which spikes occur as an essential dimension in neural representations. We present a feature-linking model (FLM) that uses the timing of spikes to encode information. The first spiking time of FLM is applied to image enhancement, and the processing mechanisms are consistent with the human visual system. The enhancement algorithm achieves boosting the details while preserving the information of the input image. Experiments are conducted to demonstrate the effectiveness of the proposed method. Results show that the proposed method is effective. PMID:26942747

  9. Special feature on imaging systems and techniques

    NASA Astrophysics Data System (ADS)

    Yang, Wuqiang; Giakos, George

    2013-07-01

    The IEEE International Conference on Imaging Systems and Techniques (IST'2012) was held in Manchester, UK, on 16-17 July 2012. The participants came from 26 countries or regions: Austria, Brazil, Canada, China, Denmark, France, Germany, Greece, India, Iran, Iraq, Italy, Japan, Korea, Latvia, Malaysia, Norway, Poland, Portugal, Sweden, Switzerland, Taiwan, Tunisia, UAE, UK and USA. The technical program of the conference consisted of a series of scientific and technical sessions, exploring physical principles, engineering and applications of new imaging systems and techniques, as reflected by the diversity of the submitted papers. Following a rigorous review process, a total of 123 papers were accepted, and they were organized into 30 oral presentation sessions and a poster session. In addition, six invited keynotes were arranged. The conference not only provided the participants with a unique opportunity to exchange ideas and disseminate research outcomes but also paved a way to establish global collaboration. Following the IST'2012, a total of 55 papers, which were technically extended substantially from their versions in the conference proceeding, were submitted as regular papers to this special feature of Measurement Science and Technology . Following a rigorous reviewing process, 25 papers have been finally accepted for publication in this special feature and they are organized into three categories: (1) industrial tomography, (2) imaging systems and techniques and (3) image processing. These papers not only present the latest developments in the field of imaging systems and techniques but also offer potential solutions to existing problems. We hope that this special feature provides a good reference for researchers who are active in the field and will serve as a catalyst to trigger further research. It has been our great pleasure to be the guest editors of this special feature. We would like to thank the authors for their contributions, without which it would

  10. Treatment with cimetidine of atypical fasciitis panniculitis syndrome.

    PubMed Central

    Naschitz, J E; Yeshurun, D; Rosner, I; Abrahamson, J E; Misselevitch, I; Boss, J H

    1990-01-01

    Three patients presented with septal fasciitis and panniculitis, associated with clinical and laboratory features which precluded straight-forward classification into eosinophilic fasciitis, localised scleroderma, or lupus erythematosus profundus. Treatment with cimetidine caused the remission of cutaneous manifestations and the extracutaneous abnormalities, such as nailfold capillary disturbances and the presence of antithyroid antibodies, improved. It is concluded that features of eosinophilic fasciitis or localised scleroderma and certain additional atypical elements should be categorised as atypical fasciitis-panniculitis syndrome. Images PMID:2241270

  11. Atypical Activation during the Embedded Figures Task as a Functional Magnetic Resonance Imaging Endophenotype of Autism

    ERIC Educational Resources Information Center

    Spencer, Michael D.; Holt, Rosemary J.; Chura, Lindsay R.; Calder, Andrew J.; Suckling, John; Bullmore, Edward T.; Baron-Cohen, Simon

    2012-01-01

    Atypical activation during the Embedded Figures Task has been demonstrated in autism, but has not been investigated in siblings or related to measures of clinical severity. We identified atypical activation during the Embedded Figures Task in participants with autism and unaffected siblings compared with control subjects in a number of temporal…

  12. Feature Evaluation for Building Facade Images - AN Empirical Study

    NASA Astrophysics Data System (ADS)

    Yang, M. Y.; Förstner, W.; Chai, D.

    2012-08-01

    The classification of building facade images is a challenging problem that receives a great deal of attention in the photogrammetry community. Image classification is critically dependent on the features. In this paper, we perform an empirical feature evaluation task for building facade images. Feature sets we choose are basic features, color features, histogram features, Peucker features, texture features, and SIFT features. We present an approach for region-wise labeling using an efficient randomized decision forest classifier and local features. We conduct our experiments with building facade image classification on the eTRIMS dataset, where our focus is the object classes building, car, door, pavement, road, sky, vegetation, and window.

  13. A hybrid features based image matching algorithm

    NASA Astrophysics Data System (ADS)

    Tu, Zhenbiao; Lin, Tao; Sun, Xiao; Dou, Hao; Ming, Delie

    2015-12-01

    In this paper, we present a novel image matching method to find the correspondences between two sets of image interest points. The proposed method is based on a revised third-order tensor graph matching method, and introduces an energy function that takes four kinds of energy term into account. The third-order tensor method can hardly deal with the situation that the number of interest points is huge. To deal with this problem, we use a potential matching set and a vote mechanism to decompose the matching task into several sub-tasks. Moreover, the third-order tensor method sometimes could only find a local optimum solution. Thus we use a cluster method to divide the feature points into some groups and only sample feature triangles between different groups, which could make the algorithm to find the global optimum solution much easier. Experiments on different image databases could prove that our new method would obtain correct matching results with relatively high efficiency.

  14. Adhesion, Biofilm Formation, and Genomic Features of Campylobacter jejuni Bf, an Atypical Strain Able to Grow under Aerobic Conditions.

    PubMed

    Bronnec, Vicky; Turoňová, Hana; Bouju, Agnès; Cruveiller, Stéphane; Rodrigues, Ramila; Demnerova, Katerina; Tresse, Odile; Haddad, Nabila; Zagorec, Monique

    2016-01-01

    Campylobacter jejuni is the leading cause of bacterial enteritis in Europe. Human campylobacteriosis cases are frequently associated to the consumption of contaminated poultry meat. To survive under environmental conditions encountered along the food chain, i.e., from poultry digestive tract its natural reservoir to the consumer's plate, this pathogen has developed adaptation mechanisms. Among those, biofilm lifestyle has been suggested as a strategy to survive in the food environment and under atmospheric conditions. Recently, the clinical isolate C. jejuni Bf has been shown to survive and grow under aerobic conditions, a property that may help this strain to better survive along the food chain. The aim of this study was to evaluate the adhesion capacity of C. jejuni Bf and its ability to develop a biofilm. C. jejuni Bf can adhere to abiotic surfaces and to human epithelial cells, and can develop biofilm under both microaerobiosis and aerobiosis. These two conditions have no influence on this strain, unlike results obtained with the reference strain C. jejuni 81-176, which harbors only planktonic cells under aerobic conditions. Compared to 81-176, the biofilm of C. jejuni Bf is more homogenous and cell motility at the bottom of biofilm was not modified whatever the atmosphere used. C. jejuni Bf whole genome sequence did not reveal any gene unique to this strain, suggesting that its unusual property does not result from acquisition of new genetic material. Nevertheless some genetic particularities seem to be shared only between Bf and few others strains. Among the main features of C. jejuni Bf genome we noticed (i) a complete type VI secretion system important in pathogenicity and environmental adaptation; (ii) a mutation in the oorD gene involved in oxygen metabolism; and (iii) the presence of an uncommon insertion of a 72 amino acid coding sequence upstream from dnaK, which is involved in stress resistance. Therefore, the atypical behavior of this strain under

  15. Adhesion, Biofilm Formation, and Genomic Features of Campylobacter jejuni Bf, an Atypical Strain Able to Grow under Aerobic Conditions

    PubMed Central

    Bronnec, Vicky; Turoňová, Hana; Bouju, Agnès; Cruveiller, Stéphane; Rodrigues, Ramila; Demnerova, Katerina; Tresse, Odile; Haddad, Nabila; Zagorec, Monique

    2016-01-01

    Campylobacter jejuni is the leading cause of bacterial enteritis in Europe. Human campylobacteriosis cases are frequently associated to the consumption of contaminated poultry meat. To survive under environmental conditions encountered along the food chain, i.e., from poultry digestive tract its natural reservoir to the consumer’s plate, this pathogen has developed adaptation mechanisms. Among those, biofilm lifestyle has been suggested as a strategy to survive in the food environment and under atmospheric conditions. Recently, the clinical isolate C. jejuni Bf has been shown to survive and grow under aerobic conditions, a property that may help this strain to better survive along the food chain. The aim of this study was to evaluate the adhesion capacity of C. jejuni Bf and its ability to develop a biofilm. C. jejuni Bf can adhere to abiotic surfaces and to human epithelial cells, and can develop biofilm under both microaerobiosis and aerobiosis. These two conditions have no influence on this strain, unlike results obtained with the reference strain C. jejuni 81-176, which harbors only planktonic cells under aerobic conditions. Compared to 81-176, the biofilm of C. jejuni Bf is more homogenous and cell motility at the bottom of biofilm was not modified whatever the atmosphere used. C. jejuni Bf whole genome sequence did not reveal any gene unique to this strain, suggesting that its unusual property does not result from acquisition of new genetic material. Nevertheless some genetic particularities seem to be shared only between Bf and few others strains. Among the main features of C. jejuni Bf genome we noticed (i) a complete type VI secretion system important in pathogenicity and environmental adaptation; (ii) a mutation in the oorD gene involved in oxygen metabolism; and (iii) the presence of an uncommon insertion of a 72 amino acid coding sequence upstream from dnaK, which is involved in stress resistance. Therefore, the atypical behavior of this strain under

  16. Imaging features of rhinosporidiosis on contrast CT

    PubMed Central

    Prabhu, Shailesh M; Irodi, Aparna; Khiangte, Hannah L; Rupa, V; Naina, P

    2013-01-01

    Context: Rhinosporidiosis is a chronic granulomatous disease endemic in certain regions of India. Computed tomography (CT) imaging appearances of rhinosporidiosis have not been previously described in the literature. Aims: To study imaging features in rhinosporidiosis with contrast-enhanced CT and elucidate its role in the evaluation of this disease. Materials and Methods: Sixteen patients with pathologically proven rhinosporidiosis were included in the study. Contrast-enhanced CT images were analyzed retrospectively and imaging findings were correlated with surgical and histopathologic findings. Results: A total of 29 lesions were found and evaluated. On contrast-enhanced CT, rhinosporidiosis was seen as moderately enhancing lobulated or irregular soft tissue mass lesions in the nasal cavity (n = 13), lesions arising in nasal cavity and extending through choana into nasopharynx (n = 5), pedunculated polypoidal lesions arising from the nasopharyngeal wall (n = 5), oropharyngeal wall (n = 2), larynx (n = 1), bronchus (n = 1), skin and subcutaneous tissue (n = 2). The inferior nasal cavity comprising nasal floor, inferior turbinate, and inferior meatus was the most common site of involvement (n = 13). Surrounding bone involvement was seen in the form of rarefaction (n = 6), partial (n = 3) or complete erosion (n = 3) of inferior turbinate, thinning of medial maxillary wall (n = 2), and septal erosion (n = 2). Nasolacrimal duct involvement was seen in four cases. Conclusions: Contrast-enhanced CT has an important role in delineating the site and extent of the disease, as well as the involvement of surrounding bone, nasolacrimal duct and tracheobronchial tree. This provides a useful roadmap prior to surgery. PMID:24347850

  17. Atypical pneumonia

    MedlinePlus

    ... that cause typical pneumonia. These include Legionella pneumophila , Mycoplasma pneumoniae , and Chlamydophila pneumoniae . Atypical pneumonia also tends to have milder symptoms than typical pneumonia. Causes Mycoplasma pneumonia is a type of atypical pneumonia. It ...

  18. Toward Automated Feature Detection in UAVSAR Images

    NASA Astrophysics Data System (ADS)

    Parker, J. W.; Donnellan, A.; Glasscoe, M. T.

    2014-12-01

    Edge detection identifies seismic or aseismic fault motion, as demonstrated in repeat-pass inteferograms obtained by the Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) program. But this identification is not robust at present: it requires a flattened background image, interpolation into missing data (holes) and outliers, and background noise that is either sufficiently small or roughly white Gaussian. Identification and mitigation of nongaussian background image noise is essential to creating a robust, automated system to search for such features. Clearly a robust method is needed for machine scanning of the thousands of UAVSAR repeat-pass interferograms for evidence of fault slip, landslides, and other local features.Empirical examination of detrended noise based on 20 km east-west profiles through desert terrain with little tectonic deformation for a suite of flight interferograms shows nongaussian characteristics. Statistical measurement of curvature with varying length scale (Allan variance) shows nearly white behavior (Allan variance slope with spatial distance from roughly -1.76 to -2) from 25 to 400 meters, deviations from -2 suggesting short-range differences (such as used in detecting edges) are often freer of noise than longer-range differences. At distances longer than 400 m the Allan variance flattens out without consistency from one interferogram to another. We attribute this additional noise afflicting difference estimates at longer distances to atmospheric water vapor and uncompensated aircraft motion.Paradoxically, California interferograms made with increasing time intervals before and after the El Mayor Cucapah earthquake (2008, M7.2, Mexico) show visually stronger and more interesting edges, but edge detection methods developed for the first year do not produce reliable results over the first two years, because longer time spans suffer reduced coherence in the interferogram. The changes over time are reflecting fault slip and block

  19. Bilateral Persistent Sciatic Artery Aneurysm Discovered by Atypical Sciatica: A Case Report

    SciTech Connect

    Mazet, Nathalie; Soulier-Guerin, Karine; Ruivard, Marc; Garcier, Jean-Marc; Boyer, Louis

    2006-12-15

    We report a case of a bilateral persistent sciatic artery aneurysm, diagnosed by atypical sciatica on computed tomography and magnetic resonance imaging. The different variants, the revealing features, and possible treatment are discussed.

  20. Variants of meningiomas: a review of imaging findings and clinical features.

    PubMed

    Kunimatsu, Akira; Kunimatsu, Natsuko; Kamiya, Kouhei; Katsura, Masaki; Mori, Harushi; Ohtomo, Kuni

    2016-07-01

    Meningiomas are common neoplasms that frequently occur in the brain and spine. Among the 15 histological subtypes of meningiomas in the WHO classification, the incidence of meningothelial meningiomas is the highest, followed by fibrous and transitional meningiomas. These three subtypes account for approximately 80 % of all meningiomas, and thus could be regarded as typical meningiomas. For this reason, other uncommon histological subtypes may be considered as imaging variants, and diagnosis is often challenging for radiologists solely based on imaging features of typical meningiomas. In addition to the histological subtypes, meningiomas arising in atypical locations could be easily mistaken for other lesions more commonly observed in those locations. The purpose of this article is to review characteristic clinical and imaging findings of uncommon meningiomas, including histological variants and meningiomas occurring in relatively rare locations. PMID:27138052

  1. Image feature extraction based multiple ant colonies cooperation

    NASA Astrophysics Data System (ADS)

    Zhang, Zhilong; Yang, Weiping; Li, Jicheng

    2015-05-01

    This paper presents a novel image feature extraction algorithm based on multiple ant colonies cooperation. Firstly, a low resolution version of the input image is created using Gaussian pyramid algorithm, and two ant colonies are spread on the source image and low resolution image respectively. The ant colony on the low resolution image uses phase congruency as its inspiration information, while the ant colony on the source image uses gradient magnitude as its inspiration information. These two ant colonies cooperate to extract salient image features through sharing a same pheromone matrix. After the optimization process, image features are detected based on thresholding the pheromone matrix. Since gradient magnitude and phase congruency of the input image are used as inspiration information of the ant colonies, our algorithm shows higher intelligence and is capable of acquiring more complete and meaningful image features than other simpler edge detectors.

  2. Investigation of atypical molten pool dynamics in tungsten carbide-cobalt during laser deposition using in-situ thermal imaging

    SciTech Connect

    Xiong Yuhong; Schoenung, Julie M.; Hofmeister, William H.; Smugeresky, John E.; Delplanque, Jean-Pierre

    2012-01-16

    An atypical ''swirling'' phenomenon observed during the laser deposition of tungsten carbide-cobalt cermets by laser engineered net shaping (LENS) was studied using in-situ high-speed thermal imaging. To provide fundamental insight into this phenomenon, the thermal behavior of pure cobalt during LENS was also investigated for comparison. Several factors were considered as the possible source of the observed differences. Of those, phase difference, material emissivity, momentum transfer, and free surface disruption from the powder jets, and, to a lesser extent, Marangoni convection were identified as the relevant mechanisms.

  3. Atypical Optic Neuritis.

    PubMed

    Gaier, Eric D; Boudreault, Katherine; Rizzo, Joseph F; Falardeau, Julie; Cestari, Dean M

    2015-12-01

    Classic demyelinative optic neuritis is associated with multiple sclerosis and typically carries a good prognosis for visual recovery. This disorder is well characterized with respect to its presentation and clinical features by baseline data obtained through the optic neuritis treatment trial and numerous other studies. Atypical optic neuritis entails clinical manifestations that deviate from this classic pattern of features. Clinical signs and symptoms that deviate from the typical presentation should prompt consideration of less common etiologies. Atypical features to consider include lack of pain, simultaneous or near-simultaneous onset, lack of response to or relapse upon tapering from corticosteroids, or optic nerve head or peripapillary hemorrhages. The most important alternative etiologies to consider and the steps towards their respective diagnostic evaluations are suggested for these atypical features. PMID:26467052

  4. Evaluation of textural features for multispectral images

    NASA Astrophysics Data System (ADS)

    Bayram, Ulya; Can, Gulcan; Duzgun, Sebnem; Yalabik, Nese

    2011-11-01

    Remote sensing is a field that has wide use, leading to the fact that it has a great importance. Therefore performance of selected features plays a great role. In order to gain some perspective on useful textural features, we have brought together state-of-art textural features in recent literature, yet to be applied in remote sensing field, as well as presenting a comparison with traditional ones. Therefore we selected most commonly used textural features in remote sensing that are grey-level co-occurrence matrix (GLCM) and Gabor features. Other selected features are local binary patterns (LBP), edge orientation features extracted after applying steerable filter, and histogram of oriented gradients (HOG) features. Color histogram feature is also used and compared. Since most of these features are histogram-based, we have compared performance of bin-by-bin comparison with a histogram comparison method named as diffusion distance method. During obtaining performance of each feature, k-nearest neighbor classification method (k-NN) is applied.

  5. Intrinsic feature-based pose measurement for imaging motion compensation

    SciTech Connect

    Baba, Justin S.; Goddard, Jr., James Samuel

    2014-08-19

    Systems and methods for generating motion corrected tomographic images are provided. A method includes obtaining first images of a region of interest (ROI) to be imaged and associated with a first time, where the first images are associated with different positions and orientations with respect to the ROI. The method also includes defining an active region in the each of the first images and selecting intrinsic features in each of the first images based on the active region. Second, identifying a portion of the intrinsic features temporally and spatially matching intrinsic features in corresponding ones of second images of the ROI associated with a second time prior to the first time and computing three-dimensional (3D) coordinates for the portion of the intrinsic features. Finally, the method includes computing a relative pose for the first images based on the 3D coordinates.

  6. The remote sensing image retrieval based on multi-feature

    NASA Astrophysics Data System (ADS)

    Duan, Jian-bo; Ma, Cai-hong; Liu, Shi-bin; Zhang, Jing

    2013-10-01

    With the rapid development of remote sensing technology and variety of earth observation satellites have been successfully launched, the volume of image datasets is growing exponentially in many application areas. The Contentbased image retrieval (CBRSIR), as an efficient means for management and utilization of the information in image database from the viewpoint of comprehension of image content, is applied on the remote sensing images retrieval. However, one kind of features always can't express the image content exactly. So, a multi-feature retrieval model based on three color features and four texture features is proposed in this paper. The experiment results show that the multifeatures model can improve the retrieval results than other model just by each singular feature.

  7. [Multiple transmission electron microscopic image stitching based on sift features].

    PubMed

    Li, Mu; Lu, Yanmeng; Han, Shuaihu; Wu, Zhuobin; Chen, Jiajing; Liu, Zhexing; Cao, Lei

    2015-08-01

    We proposed a new stitching method based on sift features to obtain an enlarged view of transmission electron microscopic (TEM) images with a high resolution. The sift features were extracted from the images, which were then combined with fitted polynomial correction field to correct the images, followed by image alignment based on the sift features. The image seams at the junction were finally removed by Poisson image editing to achieve seamless stitching, which was validated on 60 local glomerular TEM images with an image alignment error of 62.5 to 187.5 nm. Compared with 3 other stitching methods, the proposed method could effectively reduce image deformation and avoid artifacts to facilitate renal biopsy pathological diagnosis. PMID:26403733

  8. Image sharpness function based on edge feature

    NASA Astrophysics Data System (ADS)

    Jun, Ni

    2009-11-01

    Autofocus technique has been widely used in optical tracking and measure system, but it has problem that when the autofocus device should to work. So, no-reference image sharpness assessment has become an important issue. A new Sharpness Function that can estimate current frame image be in focus or not is proposed in this paper. According to current image whether in focus or not and choose the time of auto focus automatism. The algorithm measures object typical edge and edge direction, and then get image local kurtosis information to determine the degree of image sharpness. It firstly select several grads points cross the edge line, secondly calculates edge sharpness value and get the cure of the kurtosis, according the measure precision of optical-equipment, a threshold value will be set beforehand. If edge kurtosis value is more than threshold, it can conclude current frame image is in focus. Otherwise, it is out of focus. If image is out of focus, optics system then takes autofocus program. This algorithm test several thousands of digital images captured from optical tracking and measure system. The results show high correlation with subjective sharpness assessment for s images of sky object.

  9. Feature-preserving image/video compression

    NASA Astrophysics Data System (ADS)

    Al-Jawad, Naseer; Jassim, Sabah

    2005-10-01

    Advances in digital image processing, the advents of multimedia computing, and the availability of affordable high quality digital cameras have led to increased demand for digital images/videos. There has been a fast growth in the number of information systems that benefit from digital imaging techniques and present many tough challenges. In this paper e are concerned with applications for which image quality is a critical requirement. The fields of medicine, remote sensing, real time surveillance, and image-based automatic fingerprint/face identification systems are all but few examples of such applications. Medical care is increasingly dependent on imaging for diagnostics, surgery, and education. It is estimated that medium size hospitals in the US generate terabytes of MRI images and X-Ray images are generated to be stored in very large databases which are frequently accessed and searched for research and training. On the other hand, the rise of international terrorism and the growth of identity theft have added urgency to the development of new efficient biometric-based person verification/authentication systems. In future, such systems can provide an additional layer of security for online transactions or for real-time surveillance.

  10. Computer detection of features in biomedical images

    SciTech Connect

    Not Available

    1993-05-01

    Two projects under way at LLNL require the detection of spots in biomedical images: physical mapping of DNA in chromosomes, for the Human Genome Project, and finding microcalcifications, which may be an early sign of breast cancer, in mammograms. We have developed several computational algorithms to analyze these two kinds of images. The two detection methods described here use morphological imaging techniques to obtain size, shape, texture, and other information inherent in am image without trying to fit the data to a rigid mathematical model. The spot-finding algorithm has been incorporated into a DNA mapping tool for chromosomes in the metaphase of cell division; it is heavily used by researchers at the University of California, San Francisco, and may soon be distributed to other universities. Our computerized mammography work is in progress; when completed, we plan to transfer the technology to a medical imaging company.

  11. Registration of multitemporal aerial optical images using line features

    NASA Astrophysics Data System (ADS)

    Zhao, Chenyang; Goshtasby, A. Ardeshir

    2016-07-01

    Registration of multitemporal images is generally considered difficult because scene changes can occur between the times the images are obtained. Since the changes are mostly radiometric in nature, features are needed that are insensitive to radiometric differences between the images. Lines are geometric features that represent straight edges of rigid man-made structures. Because such structures rarely change over time, lines represent stable geometric features that can be used to register multitemporal remote sensing images. An algorithm to establish correspondence between lines in two images of a planar scene is introduced and formulas to relate the parameters of a homography transformation to the parameters of corresponding lines in images are derived. Results of the proposed image registration on various multitemporal images are presented and discussed.

  12. Atypical Mole (Atypical Nevus)

    MedlinePlus

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  13. Detecting Image Splicing Using Merged Features in Chroma Space

    PubMed Central

    Liu, Guangjie; Dai, Yuewei

    2014-01-01

    Image splicing is an image editing method to copy a part of an image and paste it onto another image, and it is commonly followed by postprocessing such as local/global blurring, compression, and resizing. To detect this kind of forgery, the image rich models, a feature set successfully used in the steganalysis is evaluated on the splicing image dataset at first, and the dominant submodel is selected as the first kind of feature. The selected feature and the DCT Markov features are used together to detect splicing forgery in the chroma channel, which is convinced effective in splicing detection. The experimental results indicate that the proposed method can detect splicing forgeries with lower error rate compared to the previous literature. PMID:24574877

  14. Visible and infrared image registration based on visual salient features

    NASA Astrophysics Data System (ADS)

    Wu, Feihong; Wang, Bingjian; Yi, Xiang; Li, Min; Hao, Jingya; Qin, Hanlin; Zhou, Huixin

    2015-09-01

    In order to improve the precision of visible and infrared (VIS/IR) image registration, an image registration method based on visual salient (VS) features is presented. First, a VS feature detector based on the modified visual attention model is presented to extract VS points. Because the iterative, within-feature competition method used in visual attention models is time consuming, an alternative fast visual salient (FVS) feature detector is proposed to make VS features more efficient. Then, a descriptor-rearranging (DR) strategy is adopted to describe feature points. This strategy combines information of both IR image and its negative image to overcome the contrast reverse problem between VIS and IR images, making it easier to find the corresponding points on VIS/IR images. Experiments show that both VS and FVS detectors have higher repeatability scores than scale invariant feature transform in the cases of blurring, brightness change, JPEG compression, noise, and viewpoint, except big scale change. The combination of VS detector and DR registration strategy can achieve precise image registration, but it is time-consuming. The combination of FVS detector and DR registration strategy can also reach a good registration of VIS/IR images but in a shorter time.

  15. Featured Image: The Milky Way's X

    NASA Astrophysics Data System (ADS)

    Kohler, Susanna

    2016-09-01

    The X-shaped bulge is even more evident in this image, wherein a simple exponential disk model has been subtracted off. [Adapted from Ness Lang 2016]This contrast-enhanced image of the Milky Way, observed by the Wide-Field Infrared Survey Explorer (WISE), clearly reveals that the bulge of stars at the center of our galaxy is shaped like a large X. The boxy nature of the Milky Ways bulge was revealed by satellite image in 1995, but in recent years, star counts along the line of sight toward the bulge have suggested that the bulge may be X-shaped. It was unclear whether this apparent morphology was due to the difference in the distributions of different stellar populations, or if the actual physical structure of the bulge was X-shaped. But these new WISE images, produced by astronomers Melissa Ness (Max Planck Institute for Astronomy) and Dustin Lang (University of Toronto and University of Waterloo), now provide firm evidence that the Milky Ways bulge actually is X-shaped, supplying clues as to how our galaxys center may have formed. This morphology is not uncommon; observations of other barred galaxies reveal similar X-shaped profiles. To learn more, check out the paper below!CitationMelissa Ness and Dustin Lang 2016 AJ 152 14. doi:10.3847/0004-6256/152/1/14

  16. Magnetic Resonance Imaging Findings of Early Spondylodiscitis: Interpretive Challenges and Atypical Findings

    PubMed Central

    Yeom, Jeong A; Suh, Hie Bum; Song, You Seon; Song, Jong Woon

    2016-01-01

    MR findings of early infectious spondylodiscitis are non-specific and may be confused with those of other conditions. Therefore, it is important to recognize early MR signs of conditions, such as inappreciable cortical changes in endplates, confusing marrow signal intensities of vertebral bodies, and inflammatory changes in paraspinal soft tissues, and subligamentous and epidural spaces. In addition, appreciation of direct inoculation, such as in iatrogenic spondylodiscitis may be important, because the proportion of patients who have undergone recent spine surgery or a spinal procedure is increasing. In this review, the authors focus on the MR findings of early spondylodiscitis, atypical findings of iatrogenic infection, and the differentiation between spondylodiscitis and other disease entities mimicking infection. PMID:27587946

  17. Magnetic Resonance Imaging Findings of Early Spondylodiscitis: Interpretive Challenges and Atypical Findings.

    PubMed

    Yeom, Jeong A; Lee, In Sook; Suh, Hie Bum; Song, You Seon; Song, Jong Woon

    2016-01-01

    MR findings of early infectious spondylodiscitis are non-specific and may be confused with those of other conditions. Therefore, it is important to recognize early MR signs of conditions, such as inappreciable cortical changes in endplates, confusing marrow signal intensities of vertebral bodies, and inflammatory changes in paraspinal soft tissues, and subligamentous and epidural spaces. In addition, appreciation of direct inoculation, such as in iatrogenic spondylodiscitis may be important, because the proportion of patients who have undergone recent spine surgery or a spinal procedure is increasing. In this review, the authors focus on the MR findings of early spondylodiscitis, atypical findings of iatrogenic infection, and the differentiation between spondylodiscitis and other disease entities mimicking infection. PMID:27587946

  18. Giant Cell Arteritis: An Atypical Presentation Diagnosed with the Use of MRI Imaging

    PubMed Central

    2016-01-01

    Giant cell arteritis (GCA) is the most common primary systemic vasculitis in western countries in individuals over the age of 50. It is typically characterised by the granulomatous involvement of large and medium sized blood vessels branching of the aorta with particular tendencies for involving the extracranial branches of the carotid artery. Generally the diagnosis is straightforward when characteristic symptoms such as headache, jaw claudication, or other ischemic complications are present. Atypical presentations of GCA without “overt” cranial ischemic manifestations have become increasingly recognised but we report for the first time a case of GCA presenting as mild upper abdominal pain and generalized weakness in the context of hyponatremia as the presenting manifestation of vasculitis that was subsequently diagnosed by MRI scanning. This case adds to the literature and emphasises the importance of MRI in the evaluation of GCA patients without “classic” cranial ischemic symptoms. PMID:27493825

  19. Automated Recognition of 3D Features in GPIR Images

    NASA Technical Reports Server (NTRS)

    Park, Han; Stough, Timothy; Fijany, Amir

    2007-01-01

    A method of automated recognition of three-dimensional (3D) features in images generated by ground-penetrating imaging radar (GPIR) is undergoing development. GPIR 3D images can be analyzed to detect and identify such subsurface features as pipes and other utility conduits. Until now, much of the analysis of GPIR images has been performed manually by expert operators who must visually identify and track each feature. The present method is intended to satisfy a need for more efficient and accurate analysis by means of algorithms that can automatically identify and track subsurface features, with minimal supervision by human operators. In this method, data from multiple sources (for example, data on different features extracted by different algorithms) are fused together for identifying subsurface objects. The algorithms of this method can be classified in several different ways. In one classification, the algorithms fall into three classes: (1) image-processing algorithms, (2) feature- extraction algorithms, and (3) a multiaxis data-fusion/pattern-recognition algorithm that includes a combination of machine-learning, pattern-recognition, and object-linking algorithms. The image-processing class includes preprocessing algorithms for reducing noise and enhancing target features for pattern recognition. The feature-extraction algorithms operate on preprocessed data to extract such specific features in images as two-dimensional (2D) slices of a pipe. Then the multiaxis data-fusion/ pattern-recognition algorithm identifies, classifies, and reconstructs 3D objects from the extracted features. In this process, multiple 2D features extracted by use of different algorithms and representing views along different directions are used to identify and reconstruct 3D objects. In object linking, which is an essential part of this process, features identified in successive 2D slices and located within a threshold radius of identical features in adjacent slices are linked in a

  20. Image counter-forensics based on feature injection

    NASA Astrophysics Data System (ADS)

    Iuliani, M.; Rossetto, S.; Bianchi, T.; De Rosa, Alessia; Piva, A.; Barni, M.

    2014-02-01

    Starting from the concept that many image forensic tools are based on the detection of some features revealing a particular aspect of the history of an image, in this work we model the counter-forensic attack as the injection of a specific fake feature pointing to the same history of an authentic reference image. We propose a general attack strategy that does not rely on a specific detector structure. Given a source image x and a target image y, the adversary processes x in the pixel domain producing an attacked image ~x, perceptually similar to x, whose feature f(~x) is as close as possible to f(y) computed on y. Our proposed counter-forensic attack consists in the constrained minimization of the feature distance Φ(z) =│ f(z) - f(y)│ through iterative methods based on gradient descent. To solve the intrinsic limit due to the numerical estimation of the gradient on large images, we propose the application of a feature decomposition process, that allows the problem to be reduced into many subproblems on the blocks the image is partitioned into. The proposed strategy has been tested by attacking three different features and its performance has been compared to state-of-the-art counter-forensic methods.

  1. Cell nuclear features for classification from fluorescence images

    NASA Astrophysics Data System (ADS)

    Heynen, Susanne; Hunter, Edward; Price, Jeffrey H.

    2000-04-01

    In clinical cytology, nuclear features play an important role in cell and tissue classification. To increase efficiency and decrease subjectivity of cytological results, automation of the analytic process has been proposed and discussed by many authors. This automation can be achieved by estimating the probability of occurrence of a certain class given particular features of a microscope specimen. In this paper, feature sets that might be used as inputs for mathematical cytological classification algorithms are reviewer. The primary goal was to determine the important properties of these features sets, i.e., are there mathematically efficient features that provide a more or less compete description of the cell. Under what conditions will these feature then result in optimal classification of the cells using quantitative fluorescence staining. And how would these mathematical features relate to conventional features that a human observer understands. Example human observer features are size, shape, and chromaticity o the cell nucleus while example mathematical features are image moments. If the cell image can be completely reconstructed from the feature set, then it should be possible to derive the conventional features used by human observers from the mathematical feature set for presentation to clinicians. Finally, the suitability of different mathematical decision making algorithms like probabilistic reasoning, clustering or neural networks are also briefly evaluated in the context of a mathematically complete feature set.

  2. Effect of in utero exposure to the atypical anti-psychotic risperidone on histopathological features of the rat placenta.

    PubMed

    Singh, K P; Singh, Manoj K; Gautam, Shrikant

    2016-04-01

    For clinical management of different forms of psychosis, both classical and atypical anti-psychotic drugs (APDs) are available. These drugs are widely prescribed, even during pregnancy considering their minimal extra-pyramidal side effects and teratogenic potential compared to classical APDs. Among AAPDs, risperidone (RIS) is a first-line drug of choice by physicians. The molecular weight of RIS is 410.49 g/mol; hence, it can easily cross the placental barrier and enter the foetal bloodstream. It is not known whether or not AAPDs like RIS may affect the developing placenta and foetus adversely. Reports on this issue are limited and sketchy. Therefore, this study has evaluated the effects of maternal exposure to equivalent therapeutic doses of RIS on placental growth, histopathological and cytoarchitectural changes, and to establish a relationship between placental dysfunction and foetal outcomes. Pregnant rats (n = 24) were exposed to selected doses (0.8, 1.0 and 2.0 mg/kg) of RIS from gestation days 6-21. These dams were sacrificed; their placentas and foetuses were collected, morphometrically examined and further processed for histopathological examination. This study revealed that in utero exposure to equivalent therapeutic doses of RIS during organogenesis-induced placental dystrophy (size and weight), disturbed cytoarchitectural organization (thickness of different placental layers), histopathological lesions (necrosis in trophoblast with disruption of trophoblastic septa and rupturing of maternal-foetal interface) and intrauterine growth restriction of the foetuses. It may be concluded that multifactorial mechanisms might be involved in the dysregulation of structure and function of the placenta and of poor foetal growth and development. PMID:27256515

  3. Simple Low Level Features for Image Analysis

    NASA Astrophysics Data System (ADS)

    Falcoz, Paolo

    As human beings, we perceive the world around us mainly through our eyes, and give what we see the status of “reality”; as such we historically tried to create ways of recording this reality so we could augment or extend our memory. From early attempts in photography like the image produced in 1826 by the French inventor Nicéphore Niépce (Figure 2.1) to the latest high definition camcorders, the number of recorded pieces of reality increased exponentially, posing the problem of managing all that information. Most of the raw video material produced today has lost its memory augmentation function, as it will hardly ever be viewed by any human; pervasive CCTVs are an example. They generate an enormous amount of data each day, but there is not enough “human processing power” to view them. Therefore the need for effective automatic image analysis tools is great, and a lot effort has been put in it, both from the academia and the industry. In this chapter, a review of some of the most important image analysis tools are presented.

  4. Shearlet Features for Registration of Remotely Sensed Multitemporal Images

    NASA Technical Reports Server (NTRS)

    Murphy, James M.; Le Moigne, Jacqueline

    2015-01-01

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

  5. Intrinsic Feature Pose Measurement for Awake Animal SPECT Imaging

    SciTech Connect

    Goddard Jr, James Samuel; Baba, Justin S; Lee, Seung Joon; Weisenberger, A G; Stolin, A; McKisson, J; Smith, M F

    2009-01-01

    New developments have been made in optical motion tracking for awake animal imaging that measures 3D position and orientation (pose) for a single photon emission computed tomography (SPECT) imaging system. Ongoing SPECT imaging research has been directed towards head motion measurement for brain studies in awake, unrestrained mice. In contrast to previous results using external markers, this work extracts and tracks intrinsic features from multiple camera images and computes relative pose from the tracked features over time. Motion tracking thus far has been limited to measuring extrinsic features such as retro-reflective markers applied to the mouse s head. While this approach has been proven to be accurate, the additional animal handling required to attach the markers is undesirable. A significant improvement in the procedure is achieved by measuring the pose of the head without extrinsic markers using only the external surface appearance. This approach is currently being developed with initial results presented here. The intrinsic features measurement extracts discrete, sparse natural features from 2D images such as eyes, nose, mouth and other visible structures. Stereo correspondence between features for a camera pair is determined for calculation of 3D positions. These features are also tracked over time to provide continuity for surface model fitting. Experimental results from live images are presented.

  6. Featured Image: Reddened Stars Reveal Andromeda's Dust

    NASA Astrophysics Data System (ADS)

    Kohler, Susanna

    2015-12-01

    As distant light travels on a path toward us, it can be absorbed by intervening, interstellar dust. Much work has been done to understand this dust extinction in the Milky Way, providing us with detailed information about the properties of the dust in our galaxy. Far less, however, is known about the dust extinction of other galaxies. The image above, taken with the ultraviolet space telescope GALEX, identifies the locations of four stars in the nearby Andromeda galaxy (click for a full view!) that are reddened due to extinction of their light by dust within Andromeda. In a recent study led by Geoffrey Clayton (Louisiana State University), new, high-signal-to-noise spectra were obtained for these four stars using Hubbles Space Telescope Imaging Spectrograph. These observations have allowed the authors to construct dust extinction curves to carefully study the nature of Andromedas interstellar dust. To learn about the results, see the paper below.CitationGeoffrey C. Clayton et al 2015 ApJ 815 14. doi:10.1088/0004-637X/815/1/14

  7. Featured Image: A Bubble Triggering Star Formation

    NASA Astrophysics Data System (ADS)

    Kohler, Susanna

    2016-05-01

    This remarkable false-color, mid-infrared image (click for the full view!) was produced by the Wide-field Infrared Survey Explorer (WISE). It captures a tantalizing view of Sh 2-207 and Sh 2-208, the latter of which is one of the lowest-metallicity star-forming regions in the Galaxy. In a recent study led by Chikako Yasui (University of Tokyo and the Koyama Astronomical Observatory), a team of scientists has examined this region to better understand how star formation in low-metallicity environments differs from that in the solar neighborhood. The authors analysis suggests that sequential star formation is taking place in these low-metallicity regions, triggered by an expanding bubble (the large dashed oval indicated in the image) with a ~30 pc radius. You can find out more about their study by checking out the paper below!CitationChikako Yasui et al 2016 AJ 151 115. doi:10.3847/0004-6256/151/5/115

  8. Clinical Utility of Amyloid PET Imaging in the Differential Diagnosis of Atypical Dementias and Its Impact on Caregivers.

    PubMed

    Bensaïdane, Mohamed Reda; Beauregard, Jean-Mathieu; Poulin, Stéphane; Buteau, François-Alexandre; Guimond, Jean; Bergeron, David; Verret, Louis; Fortin, Marie-Pierre; Houde, Michèle; Bouchard, Rémi W; Soucy, Jean-Paul; Laforce, Robert

    2016-04-18

    Recent studies have supported a role for amyloid positron emission tomography (PET) imaging in distinguishing Alzheimer's disease (AD) pathology from other pathological protein accumulations leading to dementia. We investigated the clinical utility of amyloid PET in the differential diagnosis of atypical dementia cases and its impact on caregivers. Using the amyloid tracer 18F-NAV4694, we prospectively scanned 28 patients (mean age 59.3 y, s.d. 5.8; mean MMSE 21.4, s.d. 6.0) with an atypical dementia syndrome. Following a comprehensive diagnostic workup (i.e., history taking, neurological examination, blood tests, neuropsychological evaluation, MRI, and FDG-PET), no certain diagnosis could be arrived at. Amyloid PET was then conducted and classified as positive or negative. Attending physicians were asked to evaluate whether this result led to a change in diagnosis or altered management. They also reported their degree of confidence in the diagnosis. Caregivers were met after disclosure of amyloid PET results and completed a questionnaire/interview to assess the impact of the scan. Our cohort was evenly divided between positive (14/28) and negative (14/28) 18F-NAV4694 cases. Amyloid PET resulted in a diagnostic change in 9/28 cases (32.1%: 17.8% changed from AD to non-AD, 14.3% from non-AD to AD). There was a 44% increase in diagnostic confidence. Altered management occurred in 71.4% (20/28) of cases. Knowledge of amyloid status improved caregivers' outcomes in all domains (anxiety, depression, disease perception, future anticipation, and quality of life). This study suggests a useful additive role for amyloid PET in atypical cases with an unclear diagnosis beyond the extensive workup of a tertiary memory clinic. Amyloid PET increased diagnostic confidence and led to clinically significant alterations in management. The information gained from that test was well received by caregivers and encouraged spending quality time with their loved ones. PMID:27104896

  9. High-resolution Urban Image Classification Using Extended Features

    SciTech Connect

    Vatsavai, Raju

    2011-01-01

    High-resolution image classification poses several challenges because the typical object size is much larger than the pixel resolution. Any given pixel (spectral features at that location) by itself is not a good indicator of the object it belongs to without looking at the broader spatial footprint. Therefore most modern machine learning approaches that are based on per-pixel spectral features are not very effective in high- resolution urban image classification. One way to overcome this problem is to extract features that exploit spatial contextual information. In this study, we evaluated several features in- cluding edge density, texture, and morphology. Several machine learning schemes were tested on the features extracted from a very high-resolution remote sensing image and results were presented.

  10. An adaptive multi-feature segmentation model for infrared image

    NASA Astrophysics Data System (ADS)

    Zhang, Tingting; Han, Jin; Zhang, Yi; Bai, Lianfa

    2016-04-01

    Active contour models (ACM) have been extensively applied to image segmentation, conventional region-based active contour models only utilize global or local single feature information to minimize the energy functional to drive the contour evolution. Considering the limitations of original ACMs, an adaptive multi-feature segmentation model is proposed to handle infrared images with blurred boundaries and low contrast. In the proposed model, several essential local statistic features are introduced to construct a multi-feature signed pressure function (MFSPF). In addition, we draw upon the adaptive weight coefficient to modify the level set formulation, which is formed by integrating MFSPF with local statistic features and signed pressure function with global information. Experimental results demonstrate that the proposed method can make up for the inadequacy of the original method and get desirable results in segmenting infrared images.

  11. Featured Image: Star Clusters in M51

    NASA Astrophysics Data System (ADS)

    Kohler, Susanna

    2016-06-01

    This beautiful mosaic of images of the Whirlpool galaxy (M51) and its companion was taken with the Advanced Camera for Surveys on the Hubble Space Telescope. This nearby, grand-design spiral galaxy has a rich population of star clusters, making it both a stunning target for imagery and an excellent resource for learning about stellar formation and evolution. In a recent study, Rupali Chandar (University of Toledo) and collaborators cataloged over 3,800 compact star clusters within this galaxy. They then used this catalog to determine the distributions for the clusters ages, masses, and sizes, which can provide important clues as to how star clusters form, evolve, and are eventually disrupted. You can read more about their study and what they discovered in the paper below.CitationRupali Chandar et al 2016 ApJ 824 71. doi:10.3847/0004-637X/824/2/71

  12. Assist features: placement, impact, and relevance for EUV imaging

    NASA Astrophysics Data System (ADS)

    Mochi, Iacopo; Philipsen, Vicky; Gallagher, Emily; Hendrickx, Eric; Lyakhova, Kateryna; Wittebrood, Friso; Schiffelers, Guido; Fliervoet, Timon; Wang, Shibing; Hsu, Stephen; Plachecki, Vince; Baron, Stan; Laenens, Bart

    2016-03-01

    Assist features are commonly used in DUV lithography to improve the lithographic process window of isolated features under illumination conditions that enable the printability of dense features. With the introduction of EUV lithography, the interaction between 13.5 nm light and the mask features generates strong mask 3D effects. On wafer, the mask 3D effects manifest as pitch-dependent best focus positions, pattern asymmetries and image contrast loss. To minimize the mask 3D effects, and enhance the lithographic process window, we explore by means of wafer print evaluation the use of assist features with different sizes and placements. The assist features are placed next to isolated features and two bar structures, consistent with theN5 (imec iN7) node dimensions for 0.33NA and we use different types of off-axis illumination . For the generic iN7 structures, wafer imaging will be compared to simulation results and an assessment of optimal assist feature configuration will be made. It is also essential to understand the potential benefit of using assist features and to weigh that benefit against the price of complexity associated with adding sub-resolution features on a production mask. To that end, we include an OPC study that compares a layout treated with assist features, to one without assist features, using full-chip complexity metrics like data size.

  13. Image mosaic method based on SIFT features of line segment.

    PubMed

    Zhu, Jun; Ren, Mingwu

    2014-01-01

    This paper proposes a novel image mosaic method based on SIFT (Scale Invariant Feature Transform) feature of line segment, aiming to resolve incident scaling, rotation, changes in lighting condition, and so on between two images in the panoramic image mosaic process. This method firstly uses Harris corner detection operator to detect key points. Secondly, it constructs directed line segments, describes them with SIFT feature, and matches those directed segments to acquire rough point matching. Finally, Ransac method is used to eliminate wrong pairs in order to accomplish image mosaic. The results from experiment based on four pairs of images show that our method has strong robustness for resolution, lighting, rotation, and scaling. PMID:24511326

  14. Breast image feature learning with adaptive deconvolutional networks

    NASA Astrophysics Data System (ADS)

    Jamieson, Andrew R.; Drukker, Karen; Giger, Maryellen L.

    2012-03-01

    Feature extraction is a critical component of medical image analysis. Many computer-aided diagnosis approaches employ hand-designed, heuristic lesion extracted features. An alternative approach is to learn features directly from images. In this preliminary study, we explored the use of Adaptive Deconvolutional Networks (ADN) for learning high-level features in diagnostic breast mass lesion images with potential application to computer-aided diagnosis (CADx) and content-based image retrieval (CBIR). ADNs (Zeiler, et. al., 2011), are recently-proposed unsupervised, generative hierarchical models that decompose images via convolution sparse coding and max pooling. We trained the ADNs to learn multiple layers of representation for two breast image data sets on two different modalities (739 full field digital mammography (FFDM) and 2393 ultrasound images). Feature map calculations were accelerated by use of GPUs. Following Zeiler et. al., we applied the Spatial Pyramid Matching (SPM) kernel (Lazebnik, et. al., 2006) on the inferred feature maps and combined this with a linear support vector machine (SVM) classifier for the task of binary classification between cancer and non-cancer breast mass lesions. Non-linear, local structure preserving dimension reduction, Elastic Embedding (Carreira-Perpiñán, 2010), was then used to visualize the SPM kernel output in 2D and qualitatively inspect image relationships learned. Performance was found to be competitive with current CADx schemes that use human-designed features, e.g., achieving a 0.632+ bootstrap AUC (by case) of 0.83 [0.78, 0.89] for an ultrasound image set (1125 cases).

  15. Featured Image: Mapping Jupiter with Hubble

    NASA Astrophysics Data System (ADS)

    Kohler, Susanna

    2016-07-01

    Zonal wind profile for Jupiter, describing the speed and direction of its winds at each latitude. [Simon et al. 2015]This global map of Jupiters surface (click for the full view!) was generated by the Hubble Outer Planet Atmospheres Legacy (OPAL) program, which aims to createnew yearly global maps for each of the outer planets. Presented in a study led by Amy Simon (NASA Goddard Space Flight Center), the map above is the first generated for Jupiter in the first year of the OPAL campaign. It provides a detailed look at Jupiters atmospheric structure including the Great Red Spot and allowed the authors to measure the speed and direction of the wind across Jupiters latitudes, constructing an updated zonal wind profile for Jupiter.In contrast to this study, the Juno mission (which will be captured into Jupiters orbit today after a 5-year journey to Jupiter!) will be focusing more on the features below Jupiters surface, studying its deep atmosphere and winds. Some of Junos primary goals are to learn about Jupiters composition, gravitational field, magnetic field, and polar magnetosphere. You can follow along with the NASATV livestream as Juno arrives at Jupiter tonight; orbit insertion coverage starts at 10:30 EDT.CitationAmy A. Simon et al 2015 ApJ 812 55. doi:10.1088/0004-637X/812/1/55

  16. Morphological Feature Extraction for Automatic Registration of Multispectral Images

    NASA Technical Reports Server (NTRS)

    Plaza, Antonio; LeMoigne, Jacqueline; Netanyahu, Nathan S.

    2007-01-01

    The task of image registration can be divided into two major components, i.e., the extraction of control points or features from images, and the search among the extracted features for the matching pairs that represent the same feature in the images to be matched. Manual extraction of control features can be subjective and extremely time consuming, and often results in few usable points. On the other hand, automated feature extraction allows using invariant target features such as edges, corners, and line intersections as relevant landmarks for registration purposes. In this paper, we present an extension of a recently developed morphological approach for automatic extraction of landmark chips and corresponding windows in a fully unsupervised manner for the registration of multispectral images. Once a set of chip-window pairs is obtained, a (hierarchical) robust feature matching procedure, based on a multiresolution overcomplete wavelet decomposition scheme, is used for registration purposes. The proposed method is validated on a pair of remotely sensed scenes acquired by the Advanced Land Imager (ALI) multispectral instrument and the Hyperion hyperspectral instrument aboard NASA's Earth Observing-1 satellite.

  17. Retinal image registration via feature-guided Gaussian mixture model.

    PubMed

    Liu, Chengyin; Ma, Jiayi; Ma, Yong; Huang, Jun

    2016-07-01

    Registration of retinal images taken at different times, from different perspectives, or with different modalities is a critical prerequisite for the diagnoses and treatments of various eye diseases. This problem can be formulated as registration of two sets of sparse feature points extracted from the given images, and it is typically solved by first creating a set of putative correspondences and then removing the false matches as well as estimating the spatial transformation between the image pairs or solved by estimating the correspondence and transformation jointly involving an iteration process. However, the former strategy suffers from missing true correspondences, and the latter strategy does not make full use of local appearance information, which may be problematic for low-quality retinal images due to a lack of reliable features. In this paper, we propose a feature-guided Gaussian mixture model (GMM) to address these issues. We formulate point registration as the estimation of a feature-guided mixture of densities: A GMM is fitted to one point set, such that both the centers and local features of the Gaussian densities are constrained to coincide with the other point set. The problem is solved under a unified maximum-likelihood framework together with an iterative expectation-maximization algorithm initialized by the confident feature correspondences, where the image transformation is modeled by an affine function. Extensive experiments on various retinal images show the robustness of our approach, which consistently outperforms other state-of-the-art methods, especially when the data is badly degraded. PMID:27409682

  18. The analysis of image feature robustness using cometcloud

    PubMed Central

    Qi, Xin; Kim, Hyunjoo; Xing, Fuyong; Parashar, Manish; Foran, David J.; Yang, Lin

    2012-01-01

    The robustness of image features is a very important consideration in quantitative image analysis. The objective of this paper is to investigate the robustness of a range of image texture features using hematoxylin stained breast tissue microarray slides which are assessed while simulating different imaging challenges including out of focus, changes in magnification and variations in illumination, noise, compression, distortion, and rotation. We employed five texture analysis methods and tested them while introducing all of the challenges listed above. The texture features that were evaluated include co-occurrence matrix, center-symmetric auto-correlation, texture feature coding method, local binary pattern, and texton. Due to the independence of each transformation and texture descriptor, a network structured combination was proposed and deployed on the Rutgers private cloud. The experiments utilized 20 randomly selected tissue microarray cores. All the combinations of the image transformations and deformations are calculated, and the whole feature extraction procedure was completed in 70 minutes using a cloud equipped with 20 nodes. Center-symmetric auto-correlation outperforms all the other four texture descriptors but also requires the longest computational time. It is roughly 10 times slower than local binary pattern and texton. From a speed perspective, both the local binary pattern and texton features provided excellent performance for classification and content-based image retrieval. PMID:23248759

  19. Fingerprint image segmentation based on multi-features histogram analysis

    NASA Astrophysics Data System (ADS)

    Wang, Peng; Zhang, Youguang

    2007-11-01

    An effective fingerprint image segmentation based on multi-features histogram analysis is presented. We extract a new feature, together with three other features to segment fingerprints. Two of these four features, each of which is related to one of the other two, are reciprocals with each other, so features are divided into two groups. These two features' histograms are calculated respectively to determine which feature group is introduced to segment the aim-fingerprint. The features could also divide fingerprints into two classes with high and low quality. Experimental results show that our algorithm could classify foreground and background effectively with lower computational cost, and it can also reduce pseudo-minutiae detected and improve the performance of AFIS.

  20. Learning Hierarchical Spectral-Spatial Features for Hyperspectral Image Classification.

    PubMed

    Zhou, Yicong; Wei, Yantao

    2016-07-01

    This paper proposes a spectral-spatial feature learning (SSFL) method to obtain robust features of hyperspectral images (HSIs). It combines the spectral feature learning and spatial feature learning in a hierarchical fashion. Stacking a set of SSFL units, a deep hierarchical model called the spectral-spatial networks (SSN) is further proposed for HSI classification. SSN can exploit both discriminative spectral and spatial information simultaneously. Specifically, SSN learns useful high-level features by alternating between spectral and spatial feature learning operations. Then, kernel-based extreme learning machine (KELM), a shallow neural network, is embedded in SSN to classify image pixels. Extensive experiments are performed on two benchmark HSI datasets to verify the effectiveness of SSN. Compared with state-of-the-art methods, SSN with a deep hierarchical architecture obtains higher classification accuracy in terms of the overall accuracy, average accuracy, and kappa ( κ ) coefficient of agreement, especially when the number of the training samples is small. PMID:26241988

  1. Featured Image: Orbiting Stars Share an Envelope

    NASA Astrophysics Data System (ADS)

    Kohler, Susanna

    2016-03-01

    This beautiful series of snapshots from a simulation (click for a better look!) shows what happens when two stars in a binary system become enclosed in the same stellar envelope. In this binary system, one of the stars has exhausted its hydrogen fuel and become a red giant, complete with an expanding stellar envelope composed of hydrogen and helium. Eventually, the envelope expands so much that the companion star falls into it, where it releases gravitational potential energy into the common envelope. A team led by Sebastian Ohlmann (Heidelberg Institute for Theoretical Studies and University of Wrzburg) recently performed hydrodynamic simulations of this process. Ohlmann and collaborators discovered that the energy release eventually triggers large-scale flow instabilities, which leads to turbulence within the envelope. This process has important consequences for how these systems next evolve (for instance, determining whether or not a supernova occurs!). You can check out the authors video of their simulated stellar inspiral below, or see their paper for more images and results from their study.CitationSebastian T. Ohlmann et al 2016 ApJ 816 L9. doi:10.3847/2041-8205/816/1/L9

  2. Featured Image: A Gap in TW Hydrae

    NASA Astrophysics Data System (ADS)

    Kohler, Susanna

    2016-04-01

    This remarkable image (click for the full view!) is a high-resolution map of the 870 m light emitted by the protoplanetary disk surrounding the young solar analog TW Hydrae. A recent study led by Sean Andrews (Harvard-Smithsonian Center for Astrophysics) presents these observations, obtained with the long-baseline configuration of the Atacama Large Millimeter/submillimeter Array (ALMA) at an unprecedented spatial resolution of ~1 AU. The data represent the distribution of millimeter-sized dust grains in this disk, revealing a beautiful concentric ring structure out to a radial distance of 60 AU from the host star. The apparent gaps in the disk could have anyof three origins:Chemical: apparent gaps can becaused by condensation fronts of volatilesMagnetic: apparent gaps can becaused by radial magnetic pressure variationsDynamic: actual gaps can becaused by the clearing of dust by young planets.For more information, check out the paper below!CitationSean M. Andrews et al 2016 ApJ 820 L40. doi:10.3847/2041-8205/820/2/L40

  3. Featured Image: Fireball After a Temporary Capture?

    NASA Astrophysics Data System (ADS)

    Kohler, Susanna

    2016-06-01

    This image of a fireball was captured in the Czech Republic by cameras at a digital autonomous observatory in the village of Kunak. This observatory is part of a network of stations known as the European Fireball Network, and this particular meteoroid detection, labeled EN130114, is notable because it has the lowest initial velocity of any natural object ever observed by the network. Led by David Clark (University of Western Ontario), the authors of a recent study speculate that before this meteoroid impacted Earth, it may have been a Temporarily Captured Orbiter (TCO). TCOs are near-Earth objects that make a few orbits of Earth before returning to heliocentric orbits. Only one has ever been observed to date, and though they are thought to make up 0.1% of all meteoroids, EN130114 is the first event ever detected that exhibits conclusive behavior of a TCO. For more information on EN130114 and why TCOs are important to study, check out the paper below!CitationDavid L. Clark et al 2016 AJ 151 135. doi:10.3847/0004-6256/151/6/135

  4. Three-dimensional floating images as overt security features

    NASA Astrophysics Data System (ADS)

    Dunn, Douglas S.; Potts, Travis L.; Lorimor, Lynn E.; Jonza, James M.; Smithson, Robert M.; Maki, Stephen P.

    2006-02-01

    3M has developed a proprietary laser process for creating three-dimensional images that appear to float above and/or below the plane of a substrate containing an array of microlenses. During the imaging process the laser records a microscopic image of the desired three-dimensional pattern in the material located at the focal point of each microlens in the array. The images exhibit motion parallax comparable to that seen from holograms and are easily visible in a wide range of ambient lighting conditions. The images are therefore similar, but not identical, to integral images, first proposed in 1908 by Lippmann. The fidelity of these floating images requires maintaining exact registration between the microlens array and the corresponding microimage array. In addition, the use of an ablative laser process for the production of the microimages enables the production of microimage features smaller than the diffraction limit (up to approximately 50,000 dpi). The images are therefore very difficult to simulate, counterfeit, or modify and are highly desirable as an overt security feature. 3M has scaled up the floating image process to produce images in Confirm TM Retroreflective Security Laminate to authenticate passports and driver's licenses and in retroreflective license plate sheeting as the Ensure TM Virtual Security Thread to authenticate vehicle registration. This allows addition of features to a secure document that are easily verifiable, using only the human eye, by a large and widely disperse population to create an identity document that is easily identified as genuine.

  5. Detection of classical 17p11.2 deletions, an atypical deletion and RAI1 alterations in patients with features suggestive of Smith–Magenis syndrome

    PubMed Central

    Vieira, Gustavo H; Rodriguez, Jayson D; Carmona-Mora, Paulina; Cao, Lei; Gamba, Bruno F; Carvalho, Daniel R; de Rezende Duarte, Andréa; Santos, Suely R; de Souza, Deise H; DuPont, Barbara R; Walz, Katherina; Moretti-Ferreira, Danilo; Srivastava, Anand K

    2012-01-01

    Smith–Magenis syndrome (SMS) is a complex disorder whose clinical features include mild to severe intellectual disability with speech delay, growth failure, brachycephaly, flat midface, short broad hands, and behavioral problems. SMS is typically caused by a large deletion on 17p11.2 that encompasses multiple genes including the retinoic acid induced 1, RAI1, gene or a mutation in the RAI1 gene. Here we have evaluated 30 patients with suspected SMS and identified SMS-associated classical 17p11.2 deletions in six patients, an atypical deletion of ∼139 kb that partially deletes the RAI1 gene in one patient, and RAI1 gene nonsynonymous alterations of unknown significance in two unrelated patients. The RAI1 mutant proteins showed no significant alterations in molecular weight, subcellular localization and transcriptional activity. Clinical features of patients with or without 17p11.2 deletions and mutations involving the RAI1 gene were compared to identify phenotypes that may be useful in diagnosing patients with SMS. PMID:21897445

  6. Invariant Feature Matching for Image Registration Application Based on New Dissimilarity of Spatial Features

    PubMed Central

    Mousavi Kahaki, Seyed Mostafa; Nordin, Md Jan; Ashtari, Amir H.; J. Zahra, Sophia

    2016-01-01

    An invariant feature matching method is proposed as a spatially invariant feature matching approach. Deformation effects, such as affine and homography, change the local information within the image and can result in ambiguous local information pertaining to image points. New method based on dissimilarity values, which measures the dissimilarity of the features through the path based on Eigenvector properties, is proposed. Evidence shows that existing matching techniques using similarity metrics—such as normalized cross-correlation, squared sum of intensity differences and correlation coefficient—are insufficient for achieving adequate results under different image deformations. Thus, new descriptor’s similarity metrics based on normalized Eigenvector correlation and signal directional differences, which are robust under local variation of the image information, are proposed to establish an efficient feature matching technique. The method proposed in this study measures the dissimilarity in the signal frequency along the path between two features. Moreover, these dissimilarity values are accumulated in a 2D dissimilarity space, allowing accurate corresponding features to be extracted based on the cumulative space using a voting strategy. This method can be used in image registration applications, as it overcomes the limitations of the existing approaches. The output results demonstrate that the proposed technique outperforms the other methods when evaluated using a standard dataset, in terms of precision-recall and corner correspondence. PMID:26985996

  7. Thermal imaging of sedimentary features on alluvial fans

    NASA Astrophysics Data System (ADS)

    Hardgrove, Craig; Moersch, Jeffrey; Whisner, Stephen

    2010-03-01

    Aerial thermal imaging is used to study grain-size distributions and induration on a wide variety of alluvial fans in the desert southwest of the United States. High-resolution aerial thermal images reveal evidence of sedimentary processes that rework and build alluvial fans, as preserved in the grain-size distributions and surface induration those processes leave behind. A catalog of constituent sedimentary features that can be identified using aerial thermal and visible imaging is provided. These features include clast-rich and clast-poor debris flows, incised channel deposits, headward-eroding gullies, sheetflood, lag surfaces, active/inactive lobes, distal sand-skirts and basin-related salt pans. Ground-based field observations of surface grain-size distributions, as well as morphologic, cross-cutting and topographic relationships were used to confirm the identifications of these feature types in remotely acquired thermal and visible images. Thermal images can also reveal trends in grain sizes between neighboring alluvial fans on a regional scale. Although inferences can be made using thermal images alone, the results from this study demonstrate that a more thorough geological interpretation of sedimentary features on an alluvial fan can be made using a combination of thermal and visible images. The results of this study have potential applications for Mars, where orbital thermal imaging might be used as a tool for evaluating constituent sedimentary processes on proposed alluvial fans.

  8. Robust Tomato Recognition for Robotic Harvesting Using Feature Images Fusion

    PubMed Central

    Zhao, Yuanshen; Gong, Liang; Huang, Yixiang; Liu, Chengliang

    2016-01-01

    Automatic recognition of mature fruits in a complex agricultural environment is still a challenge for an autonomous harvesting robot due to various disturbances existing in the background of the image. The bottleneck to robust fruit recognition is reducing influence from two main disturbances: illumination and overlapping. In order to recognize the tomato in the tree canopy using a low-cost camera, a robust tomato recognition algorithm based on multiple feature images and image fusion was studied in this paper. Firstly, two novel feature images, the  a*-component image and the I-component image, were extracted from the L*a*b* color space and luminance, in-phase, quadrature-phase (YIQ) color space, respectively. Secondly, wavelet transformation was adopted to fuse the two feature images at the pixel level, which combined the feature information of the two source images. Thirdly, in order to segment the target tomato from the background, an adaptive threshold algorithm was used to get the optimal threshold. The final segmentation result was processed by morphology operation to reduce a small amount of noise. In the detection tests, 93% target tomatoes were recognized out of 200 overall samples. It indicates that the proposed tomato recognition method is available for robotic tomato harvesting in the uncontrolled environment with low cost. PMID:26840313

  9. Feature matching method for uncorrected fisheye lens image

    NASA Astrophysics Data System (ADS)

    Liu, Na; Zhang, Baofeng; Jiao, Yingkui; Zhu, Junchao

    2016-01-01

    Traditional matching algorithms cannot be directly applied to the fisheye image matching for large distortion existing in fisheye image. Therefore, a matching algorithm based on uncorrected fisheye images is proposed. This algorithm adopts a local feature description method which combines MSER detector with CSLBP descriptor to obtain the image feature. First, the two uncorrected fisheye images captured by binocular vision system are described by the principle of epipolar constraint. Then the region detection is done with MSER and the ellipse fitting is used to the obtained regions. The MSER regions are described by CSLBP subsequently. Finally, in order to exclude the mismatching points of initial match, random sample consensus (RANSAC) algorithm has been adopted to achieve exact match. Experiments show that the method has a good effect on the uncorrected fisheye image matching.

  10. Automated feature extraction and classification from image sources

    USGS Publications Warehouse

    U.S. Geological Survey

    1995-01-01

    The U.S. Department of the Interior, U.S. Geological Survey (USGS), and Unisys Corporation have completed a cooperative research and development agreement (CRADA) to explore automated feature extraction and classification from image sources. The CRADA helped the USGS define the spectral and spatial resolution characteristics of airborne and satellite imaging sensors necessary to meet base cartographic and land use and land cover feature classification requirements and help develop future automated geographic and cartographic data production capabilities. The USGS is seeking a new commercial partner to continue automated feature extraction and classification research and development.

  11. Imaging features of Burkitt lymphoma in pediatric patients

    PubMed Central

    Derinkuyu, Betül Emine; Boyunağa, Öznur; Öztunalı, Çiğdem; Tekkeşin, Funda; Damar, Çağrı; Alımlı, Ayşe Gül; Okur, Arzu

    2016-01-01

    Burkitt lymphoma is an aggressive and rapidly growing tumor that is curable and highly sensitive to chemotherapy. It can affect almost every tissue in the body, producing various clinical presentations and imaging appearances, according to the predilection of the different subtypes for certain sites. Awareness of its diagnostically specific imaging appearances plays an important role in rapid detection and treatment. In this pictorial review, we aimed to identify the most common imaging features of Burkitt lymphoma in pediatric patients. PMID:26611257

  12. Atypical Teratomas of the Pineal

    PubMed Central

    Lewis, I.; Baxter, D. W.; Stratford, J. G.

    1963-01-01

    Atypical teratomas of the pineal were studied pathologically and clinically, and five illustrative cases are described. The results of three postmortem examinations are available, while two of the patients are living, one leading a normal life. Pathological verification revealed that two had suprasellar “ectopic” pinealomas. One neoplasm was located in the pineal (collicular) region. The histology of the tumours was identical, consisting of small cells resembling lymphocytes and large cells with prominent nucleoli and mitoses. This feature plus the midline location led to adoption of the term “atypical teratoma”. Patients with collicular pinealomas presented with headache, vomiting, papilledema, Parinaud's syndrome and, rarely, nystagmus retractorius. Diabetes insipidus, visual difficulty and hypopituitarism were characteristic features in those with suprasellar neoplasms. Treatment of collicular pinealoma has consisted of the use of a palliative shunt followed by a course of radiation. Chiasmal decompression and radiation have produced favourable results in patients with suprasellar pinealoma. ImagesFig. 1Fig. 2Fig. 3Fig. 4Fig. 5Fig. 6Fig. 7Fig. 8Fig. 9Fig. 10Fig. 11Fig. 12 PMID:20327617

  13. A novel feature point matching method of remote sensing images

    NASA Astrophysics Data System (ADS)

    Xu, Yuanquan; Wang, Han; Zhang, Xubing; Wang, ShaoJun

    2015-12-01

    The method of feature-based registration has been successful applied in registration of multi-source remote sensing images. Unfortunately, the mismatching still exists due to the complex textures, spectrum variation, nonlinear distortion and the large scale change. In this paper, we proposed a novel feature point matching method of multi-source remote sensing images. Firstly, the Fast-Hessian detector is to extract the feature points which are described by the SURF descriptor in the following step. After that, we analyze the local neighborhood structures of the feature points, and formulate point matching as an optimization problem to preserve local neighborhood structures. The shape context distances of the feature points are utilized to initialize matching probability matrix. Then relaxation labeling is adopted to update the probability matrix and refine the matching, which is aimed to maximize the value of the object function deduced based on preserving local neighborhood structures. Subsequently, the mismatching elimination method based on affine transformation and distance measurement is used to eliminate the residual mismatching points. During the abovementioned matching produce, the multi-resolution analysis method is adopted to decrease the scale difference between the multi-source remote sensing images. Also the mutual information method is utilized to match the feature points of the down sampling and the original images. The experimental results are shown that the proposed method was robust and efficient for registration of multi-source remote sensing images.

  14. Improvements in intrinsic feature pose measurement for awake animal imaging

    SciTech Connect

    J.S. Goddard, J.S. Baba, S.J. Lee, A.G. Weisenberger, A. Stolin, J. McKisson, M.F. Smith

    2011-06-01

    Development has continued with intrinsic feature optical motion tracking for awake animal imaging to measure 3D position and orientation (pose) for motion compensated reconstruction. Prior imaging results have been directed towards head motion measurement for SPECT brain studies in awake unrestrained mice. This work improves on those results in extracting and tracking intrinsic features from multiple camera images and computing pose changes from the tracked features over time. Previously, most motion tracking for 3D imaging has been limited to measuring extrinsic features such as retro-reflective markers applied to an animal's head. While this approach has been proven to be accurate, the use of external markers is undesirable for several reasons. The intrinsic feature approach has been further developed from previous work to provide full pose measurements for a live mouse scan. Surface feature extraction, matching, and pose change calculation with point tracking and accuracy results are described. Experimental pose calculation and 3D reconstruction results from live images are presented.

  15. Improvements in Intrinsic Feature Pose Measurement for Awake Animal Imaging

    SciTech Connect

    Goddard Jr, James Samuel; Baba, Justin S; Lee, Seung Joon; Weisenberger, A G; McKisson, J; Smith, M F; Stolin, Alexander

    2010-01-01

    Development has continued with intrinsic feature optical motion tracking for awake animal imaging to measure 3D position and orientation (pose) for motion compensated reconstruction. Prior imaging results have been directed towards head motion measurement for SPECT brain studies in awake unrestrained mice. This work improves on those results in extracting and tracking intrinsic features from multiple camera images and computing pose changes from the tracked features over time. Previously, most motion tracking for 3D imaging has been limited to measuring extrinsic features such as retro-reflective markers applied to an animal s head. While this approach has been proven to be accurate, the use of external markers is undesirable for several reasons. The intrinsic feature approach has been further developed from previous work to provide full pose measurements for a live mouse scan. Surface feature extraction, matching, and pose change calculation with point tracking and accuracy results are described. Experimental pose calculation and 3D reconstruction results from live images are presented.

  16. A high performance parallel computing architecture for robust image features

    NASA Astrophysics Data System (ADS)

    Zhou, Renyan; Liu, Leibo; Wei, Shaojun

    2014-03-01

    A design of parallel architecture for image feature detection and description is proposed in this article. The major component of this architecture is a 2D cellular network composed of simple reprogrammable processors, enabling the Hessian Blob Detector and Haar Response Calculation, which are the most computing-intensive stage of the Speeded Up Robust Features (SURF) algorithm. Combining this 2D cellular network and dedicated hardware for SURF descriptors, this architecture achieves real-time image feature detection with minimal software in the host processor. A prototype FPGA implementation of the proposed architecture achieves 1318.9 GOPS general pixel processing @ 100 MHz clock and achieves up to 118 fps in VGA (640 × 480) image feature detection. The proposed architecture is stand-alone and scalable so it is easy to be migrated into VLSI implementation.

  17. Direct extraction of topographic features from gray scale haracter images

    SciTech Connect

    Seong-Whan Lee; Young Joon Kim

    1994-12-31

    Optical character recognition (OCR) traditionally applies to binary-valued imagery although text is always scanned and stored in gray scale. However, binarization of multivalued image may remove important topological information from characters and introduce noise to character background. In order to avoid this problem, it is indispensable to develop a method which can minimize the information loss due to binarization by extracting features directly from gray scale character images. In this paper, we propose a new method for the direct extraction of topographic features from gray scale character images. By comparing the proposed method with the Wang and Pavlidis`s method we realized that the proposed method enhanced the performance of topographic feature extraction by computing the directions of principal curvature efficiently and prevented the extraction of unnecessary features. We also show that the proposed method is very effective for gray scale skeletonization compared to Levi and Montanari`s method.

  18. Face Recognition with Multi-Resolution Spectral Feature Images

    PubMed Central

    Sun, Zhan-Li; Lam, Kin-Man; Dong, Zhao-Yang; Wang, Han; Gao, Qing-Wei; Zheng, Chun-Hou

    2013-01-01

    The one-sample-per-person problem has become an active research topic for face recognition in recent years because of its challenges and significance for real-world applications. However, achieving relatively higher recognition accuracy is still a difficult problem due to, usually, too few training samples being available and variations of illumination and expression. To alleviate the negative effects caused by these unfavorable factors, in this paper we propose a more accurate spectral feature image-based 2DLDA (two-dimensional linear discriminant analysis) ensemble algorithm for face recognition, with one sample image per person. In our algorithm, multi-resolution spectral feature images are constructed to represent the face images; this can greatly enlarge the training set. The proposed method is inspired by our finding that, among these spectral feature images, features extracted from some orientations and scales using 2DLDA are not sensitive to variations of illumination and expression. In order to maintain the positive characteristics of these filters and to make correct category assignments, the strategy of classifier committee learning (CCL) is designed to combine the results obtained from different spectral feature images. Using the above strategies, the negative effects caused by those unfavorable factors can be alleviated efficiently in face recognition. Experimental results on the standard databases demonstrate the feasibility and efficiency of the proposed method. PMID:23418451

  19. Predicting beef tenderness using color and multispectral image texture features.

    PubMed

    Sun, X; Chen, K J; Maddock-Carlin, K R; Anderson, V L; Lepper, A N; Schwartz, C A; Keller, W L; Ilse, B R; Magolski, J D; Berg, E P

    2012-12-01

    The objective of this study was to investigate the usefulness of raw meat surface characteristics (texture) in predicting cooked beef tenderness. Color and multispectral texture features, including 4 different wavelengths and 217 image texture features, were extracted from 2 laboratory-based multispectral camera imaging systems. Steaks were segregated into tough and tender classification groups based on Warner-Bratzler shear force. The texture features were submitted to STEPWISE multiple regression and support vector machine (SVM) analyses to establish prediction models for beef tenderness. A subsample (80%) of tender or tough classified steaks were used to train models which were then validated on the remaining (20%) test steaks. For color images, the SVM model correctly identified tender steaks with 100% accurately while the STEPWISE equation identified 94.9% of the tender steaks correctly. For multispectral images, the SVM model predicted 91% and STEPWISE predicted 87% average accuracy of beef tender. PMID:22647652

  20. Automated Image Registration Using Morphological Region of Interest Feature Extraction

    NASA Technical Reports Server (NTRS)

    Plaza, Antonio; LeMoigne, Jacqueline; Netanyahu, Nathan S.

    2005-01-01

    With the recent explosion in the amount of remotely sensed imagery and the corresponding interest in temporal change detection and modeling, image registration has become increasingly important as a necessary first step in the integration of multi-temporal and multi-sensor data for applications such as the analysis of seasonal and annual global climate changes, as well as land use/cover changes. The task of image registration can be divided into two major components: (1) the extraction of control points or features from images; and (2) the search among the extracted features for the matching pairs that represent the same feature in the images to be matched. Manual control feature extraction can be subjective and extremely time consuming, and often results in few usable points. Automated feature extraction is a solution to this problem, where desired target features are invariant, and represent evenly distributed landmarks such as edges, corners and line intersections. In this paper, we develop a novel automated registration approach based on the following steps. First, a mathematical morphology (MM)-based method is used to obtain a scale-orientation morphological profile at each image pixel. Next, a spectral dissimilarity metric such as the spectral information divergence is applied for automated extraction of landmark chips, followed by an initial approximate matching. This initial condition is then refined using a hierarchical robust feature matching (RFM) procedure. Experimental results reveal that the proposed registration technique offers a robust solution in the presence of seasonal changes and other interfering factors. Keywords-Automated image registration, multi-temporal imagery, mathematical morphology, robust feature matching.

  1. Histopathological Image Classification Using Discriminative Feature-Oriented Dictionary Learning.

    PubMed

    Vu, Tiep Huu; Mousavi, Hojjat Seyed; Monga, Vishal; Rao, Ganesh; Rao, U K Arvind

    2016-03-01

    In histopathological image analysis, feature extraction for classification is a challenging task due to the diversity of histology features suitable for each problem as well as presence of rich geometrical structures. In this paper, we propose an automatic feature discovery framework via learning class-specific dictionaries and present a low-complexity method for classification and disease grading in histopathology. Essentially, our Discriminative Feature-oriented Dictionary Learning (DFDL) method learns class-specific dictionaries such that under a sparsity constraint, the learned dictionaries allow representing a new image sample parsimoniously via the dictionary corresponding to the class identity of the sample. At the same time, the dictionary is designed to be poorly capable of representing samples from other classes. Experiments on three challenging real-world image databases: 1) histopathological images of intraductal breast lesions, 2) mammalian kidney, lung and spleen images provided by the Animal Diagnostics Lab (ADL) at Pennsylvania State University, and 3) brain tumor images from The Cancer Genome Atlas (TCGA) database, reveal the merits of our proposal over state-of-the-art alternatives. Moreover, we demonstrate that DFDL exhibits a more graceful decay in classification accuracy against the number of training images which is highly desirable in practice where generous training is often not available. PMID:26513781

  2. Integration of Image-Derived and Pos-Derived Features for Image Blur Detection

    NASA Astrophysics Data System (ADS)

    Teo, Tee-Ann; Zhan, Kai-Zhi

    2016-06-01

    The image quality plays an important role for Unmanned Aerial Vehicle (UAV)'s applications. The small fixed wings UAV is suffering from the image blur due to the crosswind and the turbulence. Position and Orientation System (POS), which provides the position and orientation information, is installed onto an UAV to enable acquisition of UAV trajectory. It can be used to calculate the positional and angular velocities when the camera shutter is open. This study proposes a POS-assisted method to detect the blur image. The major steps include feature extraction, blur image detection and verification. In feature extraction, this study extracts different features from images and POS. The image-derived features include mean and standard deviation of image gradient. For POS-derived features, we modify the traditional degree-of-linear-blur (blinear) method to degree-of-motion-blur (bmotion) based on the collinear condition equations and POS parameters. Besides, POS parameters such as positional and angular velocities are also adopted as POS-derived features. In blur detection, this study uses Support Vector Machines (SVM) classifier and extracted features (i.e. image information, POS data, blinear and bmotion) to separate blur and sharp UAV images. The experiment utilizes SenseFly eBee UAV system. The number of image is 129. In blur image detection, we use the proposed degree-of-motion-blur and other image features to classify the blur image and sharp images. The classification result shows that the overall accuracy using image features is only 56%. The integration of image-derived and POS-derived features have improved the overall accuracy from 56% to 76% in blur detection. Besides, this study indicates that the performance of the proposed degree-of-motion-blur is better than the traditional degree-of-linear-blur.

  3. Effective feature selection for image steganalysis using extreme learning machine

    NASA Astrophysics Data System (ADS)

    Feng, Guorui; Zhang, Haiyan; Zhang, Xinpeng

    2014-11-01

    Image steganography delivers secret data by slight modifications of the cover. To detect these data, steganalysis tries to create some features to embody the discrepancy between the cover and steganographic images. Therefore, the urgent problem is how to design an effective classification architecture for given feature vectors extracted from the images. We propose an approach to automatically select effective features based on the well-known JPEG steganographic methods. This approach, referred to as extreme learning machine revisited feature selection (ELM-RFS), can tune input weights in terms of the importance of input features. This idea is derived from cross-validation learning and one-dimensional (1-D) search. While updating input weights, we seek the energy decreasing direction using the leave-one-out (LOO) selection. Furthermore, we optimize the 1-D energy function instead of directly discarding the least significant feature. Since recent Liu features can gain considerable low detection errors compared to a previous JPEG steganalysis, the experimental results demonstrate that the new approach results in less classification error than other classifiers such as SVM, Kodovsky ensemble classifier, direct ELM-LOO learning, kernel ELM, and conventional ELM in Liu features. Furthermore, ELM-RFS achieves a similar performance with a deep Boltzmann machine using less training time.

  4. Stress fractures: pathophysiology, clinical presentation, imaging features, and treatment options.

    PubMed

    Matcuk, George R; Mahanty, Scott R; Skalski, Matthew R; Patel, Dakshesh B; White, Eric A; Gottsegen, Christopher J

    2016-08-01

    Stress fracture, in its most inclusive description, includes both fatigue and insufficiency fracture. Fatigue fractures, sometimes equated with the term "stress fractures," are most common in runners and other athletes and typically occur in the lower extremities. These fractures are the result of abnormal, cyclical loading on normal bone leading to local cortical resorption and fracture. Insufficiency fractures are common in elderly populations, secondary to osteoporosis, and are typically located in and around the pelvis. They are a result of normal or traumatic loading on abnormal bone. Subchondral insufficiency fractures of the hip or knee may cause acute pain that may present in the emergency setting. Medial tibial stress syndrome is a type of stress injury of the tibia related to activity and is a clinical syndrome encompassing a range of injuries from stress edema to frank-displaced fracture. Atypical subtrochanteric femoral fracture associated with long-term bisphosphonate therapy is also a recently discovered entity that needs early recognition to prevent progression to a complete fracture. Imaging recommendations for evaluation of stress fractures include initial plain radiographs followed, if necessary, by magnetic resonance imaging (MRI), which is preferred over computed tomography (CT) and bone scintigraphy. Radiographs are the first-line modality and may reveal linear sclerosis and periosteal reaction prior to the development of a frank fracture. MRI is highly sensitive with findings ranging from periosteal edema to bone marrow and intracortical signal abnormality. Additionally, a brief description of relevant clinical management of stress fractures is included. PMID:27002328

  5. Optimal feature extraction for segmentation of Diesel spray images.

    PubMed

    Payri, Francisco; Pastor, José V; Palomares, Alberto; Juliá, J Enrique

    2004-04-01

    A one-dimensional simplification, based on optimal feature extraction, of the algorithm based on the likelihood-ratio test method (LRT) for segmentation in colored Diesel spray images is presented. If the pixel values of the Diesel spray and the combustion images are represented in RGB space, in most cases they are distributed in an area with a given so-called privileged direction. It is demonstrated that this direction permits optimal feature extraction for one-dimensional segmentation in the Diesel spray images, and some of its advantages compared with more-conventional one-dimensional simplification methods, including considerably reduced computational cost while accuracy is maintained within more than reasonable limits, are presented. The method has been successfully applied to images of Diesel sprays injected at room temperature as well as to images of sprays with evaporation and combustion. It has proved to be valid for several cameras and experimental arrangements. PMID:15074419

  6. Categorizing biomedicine images using novel image features and sparse coding representation

    PubMed Central

    2013-01-01

    Background Images embedded in biomedical publications carry rich information that often concisely summarize key hypotheses adopted, methods employed, or results obtained in a published study. Therefore, they offer valuable clues for understanding main content in a biomedical publication. Prior studies have pointed out the potential of mining images embedded in biomedical publications for automatically understanding and retrieving such images' associated source documents. Within the broad area of biomedical image processing, categorizing biomedical images is a fundamental step for building many advanced image analysis, retrieval, and mining applications. Similar to any automatic categorization effort, discriminative image features can provide the most crucial aid in the process. Method We observe that many images embedded in biomedical publications carry versatile annotation text. Based on the locations of and the spatial relationships between these text elements in an image, we thus propose some novel image features for image categorization purpose, which quantitatively characterize the spatial positions and distributions of text elements inside a biomedical image. We further adopt a sparse coding representation (SCR) based technique to categorize images embedded in biomedical publications by leveraging our newly proposed image features. Results we randomly selected 990 images of the JPG format for use in our experiments where 310 images were used as training samples and the rest were used as the testing cases. We first segmented 310 sample images following the our proposed procedure. This step produced a total of 1035 sub-images. We then manually labeled all these sub-images according to the two-level hierarchical image taxonomy proposed by [1]. Among our annotation results, 316 are microscopy images, 126 are gel electrophoresis images, 135 are line charts, 156 are bar charts, 52 are spot charts, 25 are tables, 70 are flow charts, and the remaining 155 images are

  7. NSCLC tumor shrinkage prediction using quantitative image features.

    PubMed

    Hunter, Luke A; Chen, Yi Pei; Zhang, Lifei; Matney, Jason E; Choi, Haesun; Kry, Stephen F; Martel, Mary K; Stingo, Francesco; Liao, Zhongxing; Gomez, Daniel; Yang, Jinzhong; Court, Laurence E

    2016-04-01

    The objective of this study was to develop a quantitative image feature model to predict non-small cell lung cancer (NSCLC) volume shrinkage from pre-treatment CT images. 64 stage II-IIIB NSCLC patients with similar treatments were all imaged using the same CT scanner and protocol. For each patient, the planning gross tumor volume (GTV) was deformed onto the week 6 treatment image, and tumor shrinkage was quantified as the deformed GTV volume divided by the planning GTV volume. Geometric, intensity histogram, absolute gradient image, co-occurrence matrix, and run-length matrix image features were extracted from each planning GTV. Prediction models were generated using principal component regression with simulated annealing subset selection. Performance was quantified using the mean squared error (MSE) between the predicted and observed tumor shrinkages. Permutation tests were used to validate the results. The optimal prediction model gave a strong correlation between the observed and predicted tumor shrinkages with r=0.81 and MSE=8.60×10(-3). Compared to predictions based on the mean population shrinkage this resulted in a 2.92 fold reduction in MSE. In conclusion, this study indicated that quantitative image features extracted from existing pre-treatment CT images can successfully predict tumor shrinkage and provide additional information for clinical decisions regarding patient risk stratification, treatment, and prognosis. PMID:26878137

  8. Coevolving feature extraction agents for target recognition in SAR images

    NASA Astrophysics Data System (ADS)

    Bhanu, Bir; Krawiec, Krzysztof

    2003-09-01

    This paper describes a novel evolutionary method for automatic induction of target recognition procedures from examples. The learning process starts with training data containing SAR images with labeled targets and consists in coevolving the population of feature extraction agents that cooperate to build an appropriate representation of the input image. Features extracted by a team of cooperating agents are used to induce a machine learning classifier that is responsible for making the final decision of recognizing a target in a SAR image. Each agent (individual) contains feature extraction procedure encoded according to the principles of linear genetic programming (LGP). Like 'plain' genetic programming, in LGP an agent's genome encodes a program that is executed and tested on the set of training images during the fitness calculation. The program is a sequence of calls to the library of parameterized operations, including, but not limited to, global and local image processing operations, elementary feature extraction, and logic and arithmetic operations. Particular calls operate on working variables that enable the program to store intermediate results, and therefore design complex features. This paper contains detailed description of the learning and recognition methodology outlined here. In experimental part, we report and analyze the results obtained when testing the proposed approach for SAR target recognition using MSTAR database.

  9. Image Recommendation Algorithm Using Feature-Based Collaborative Filtering

    NASA Astrophysics Data System (ADS)

    Kim, Deok-Hwan

    As the multimedia contents market continues its rapid expansion, the amount of image contents used in mobile phone services, digital libraries, and catalog service is increasing remarkably. In spite of this rapid growth, users experience high levels of frustration when searching for the desired image. Even though new images are profitable to the service providers, traditional collaborative filtering methods cannot recommend them. To solve this problem, in this paper, we propose feature-based collaborative filtering (FBCF) method to reflect the user's most recent preference by representing his purchase sequence in the visual feature space. The proposed approach represents the images that have been purchased in the past as the feature clusters in the multi-dimensional feature space and then selects neighbors by using an inter-cluster distance function between their feature clusters. Various experiments using real image data demonstrate that the proposed approach provides a higher quality recommendation and better performance than do typical collaborative filtering and content-based filtering techniques.

  10. Preliminary investigation into sources of uncertainty in quantitative imaging features.

    PubMed

    Fave, Xenia; Cook, Molly; Frederick, Amy; Zhang, Lifei; Yang, Jinzhong; Fried, David; Stingo, Francesco; Court, Laurence

    2015-09-01

    Several recent studies have demonstrated the potential for quantitative imaging features to classify non-small cell lung cancer (NSCLC) patients as high or low risk. However applying the results from one institution to another has been difficult because of the variations in imaging techniques and feature measurement. Our study was designed to determine the effect of some of these sources of uncertainty on image features extracted from computed tomography (CT) images of non-small cell lung cancer (NSCLC) tumors. CT images from 20 NSCLC patients were obtained for investigating the impact of four sources of uncertainty: Two region of interest (ROI) selection conditions (breathing phase and single-slice vs. whole volume) and two imaging protocol parameters (peak tube voltage and current). Texture values did not vary substantially with the choice of breathing phase; however, almost half (12 out of 28) of the measured textures did change significantly when measured from the average images compared to the end-of-exhale phase. Of the 28 features, 8 showed a significant variation when measured from the largest cross sectional slice compared to the entire tumor, but 14 were correlated to the entire tumor value. While simulating a decrease in tube voltage had a negligible impact on texture features, simulating a decrease in mA resulted in significant changes for 13 of the 23 texture values. Our results suggest that substantial variation exists when textures are measured under different conditions, and thus the development of a texture analysis standard would be beneficial for comparing features between patients and institutions. PMID:26004695

  11. Feature maps driven no-reference image quality prediction of authentically distorted images

    NASA Astrophysics Data System (ADS)

    Ghadiyaram, Deepti; Bovik, Alan C.

    2015-03-01

    Current blind image quality prediction models rely on benchmark databases comprised of singly and synthetically distorted images, thereby learning image features that are only adequate to predict human perceived visual quality on such inauthentic distortions. However, real world images often contain complex mixtures of multiple distortions. Rather than a) discounting the effect of these mixtures of distortions on an image's perceptual quality and considering only the dominant distortion or b) using features that are only proven to be efficient for singly distorted images, we deeply study the natural scene statistics of authentically distorted images, in different color spaces and transform domains. We propose a feature-maps-driven statistical approach which avoids any latent assumptions about the type of distortion(s) contained in an image, and focuses instead on modeling the remarkable consistencies in the scene statistics of real world images in the absence of distortions. We design a deep belief network that takes model-based statistical image features derived from a very large database of authentically distorted images as input and discovers good feature representations by generalizing over different distortion types, mixtures, and severities, which are later used to learn a regressor for quality prediction. We demonstrate the remarkable competence of our features for improving automatic perceptual quality prediction on a benchmark database and on the newly designed LIVE Authentic Image Quality Challenge Database and show that our approach of combining robust statistical features and the deep belief network dramatically outperforms the state-of-the-art.

  12. Suprasellar masses in children: Characteristic MR imaging features.

    PubMed

    Yildiz, Adalet Elcin; Oguz, Kader Karli; Fitoz, Suat

    2016-07-01

    Pediatric suprasellar masses are unique in their clinical presentation and imaging features. The differential diagnosis, incidence, surgical approach and adjuvant treatment options differ from adult tumors. Magnetic resonance (MR) imaging is fundamental in preoperative evaluation and provides detailed information about the suprasellar region. In this article, we review the characteristic MR imaging findings of common suprasellar masses in children. We also briefly discuss useful MR imaging sequences and planes used in the initial evaluation of a pediatric suprasellar mass and clinical findings at presentation. PMID:27131616

  13. Combinational feature optimization for classification of lung tissue images

    NASA Astrophysics Data System (ADS)

    Samala, Ravi K.; Zhukov, Tatyana; Zhang, Jianying; Tockman, Melvyn; Qian, Wei

    2010-03-01

    A novel approach to feature optimization for classification of lung carcinoma using tissue images is presented. The methodology uses a combination of three characteristics of computational features: F-measure, which is a representation of each feature towards classification, inter-correlation between features and pathology based information. The metadata provided from pathological parameters is used for mapping between computational features and biological information. Multiple regression analysis maps each category of features based on how pathology information is correlated with the size and location of cancer. Relatively the computational features represented the tumor size better than the location of the cancer. Based on the three criteria associated with the features, three sets of feature subsets with individual validation are evaluated to select the optimum feature subset. Based on the results from the three stages, the knowledgebase produces the best subset of features. An improvement of 5.5% was observed for normal Vs all abnormal cases with Az value of 0.731 and 74/114 correctly classified. The best Az value of 0.804 with 66/84 correct classification and improvement of 21.6% was observed for normal Vs adenocarcinoma.

  14. Unsupervised Feature Learning for High-Resolution Satellite Image Classification

    SciTech Connect

    Cheriyadat, Anil M

    2013-01-01

    The rich data provided by high-resolution satellite imagery allow us to directly model geospatial neighborhoods by understanding their spatial and structural patterns. In this paper we explore an unsupervised feature learning approach to model geospatial neighborhoods for classification purposes. While pixel and object based classification approaches are widely used for satellite image analysis, often these approaches exploit the high-fidelity image data in a limited way. In this paper we extract low-level features to characterize the local neighborhood patterns. We exploit the unlabeled feature measurements in a novel way to learn a set of basis functions to derive new features. The derived sparse feature representation obtained by encoding the measured features in terms of the learned basis function set yields superior classification performance. We applied our technique on two challenging image datasets: ORNL dataset representing one-meter spatial resolution satellite imagery representing five land-use categories and, UCMERCED dataset consisting of 21 different categories representing sub-meter resolution overhead imagery. Our results are highly promising and, in the case of UCMERCED dataset we outperform the best results obtained for this dataset. We show that our feature extraction and learning methods are highly effective in developing a detection system that can be used to automatically scan large-scale high-resolution satellite imagery for detecting large-facility.

  15. Atypical histiocytosis in the lung

    PubMed Central

    Cao, Weijun; Zhang, Rongxuan; Zhou, Ying; Xu, Jinfu; Garfield, David H.

    2013-01-01

    Objective To report a rare case of atypical histiocytic tumor of the lung with a review of literature. Methods The clinical materials were noted. Literature related to this condition from the past 50 years was reviewed from the group of histiocytic tumors. Results and conclusions Clinical manifestations were non-specific. The imaging characteristics of our case were infiltrative lesions with multiple cysts in both lungs. Pathology showed nodular proliferation of atypical cells. Immunohistochemistry suggested a histiocytic origin of the infiltrating atypical cells. Because the pathological findings did not fall into any particular category of typical histiocytic tumors, the final diagnosis was atypical histiocytic tumor. The presentation of atypical histiocytic tumor of the lungs, only, with infiltrative lesions and multiple air cysts seems very rare, with pathological examination being “gold standard” for the diagnosis. PMID:23991320

  16. Semi-supervised feature learning for hyperspectral image classification

    NASA Astrophysics Data System (ADS)

    Zhang, Pengfei; Cao, Liujuan; Wang, Cheng; Li, Jonathan

    2016-03-01

    Hyperspectral image has high-dimensional Spectral-spatial features, those features with some noisy and redundant information. Since redundant features can have significant adverse effect on learning performance. So efficient and robust feature selection methods are make the best of labeled and unlabeled points to extract meaningful features and eliminate noisy ones. On the other hand, obtaining sufficient accurate labeled data is either impossible or expensive. In order to take advantage of both precious labeled and unlabeled data points, in this paper, we propose a new semisupervised feature selection method, Firstly, we use labeled points are to enlarge the margin between data points from different classes; Secondly, we use unlabeled points to find the local structure of the data space; Finally, we compare our proposed algorithm with Fisher score, PCA and Laplacian score on HSI classification. Experimental results on benchmark hyperspectral data sets demonstrate the efficiency and effectiveness of our proposed algorithm.

  17. Feature-Based Digital Watermarking for Remote Sensing Images

    NASA Astrophysics Data System (ADS)

    Hsu, P.-H.; Chen, C.-C.

    2012-08-01

    With the rapid development of information and communication technology, people can acquire and distribute many kinds of digital data more conveniently than before. The consequence is that the "copyright protection" which prevents digital data from been duplicated illegally should be paid much more attention. Digital watermarking is the process of embedding visible or invisible information into a digital signal which may be used to verify its authenticity or the identity of its owners. In the past, digital watermarking technology has been successfully applied to the "copyright protection" of multimedia data, however the researches and applications of applying digital watermarking to geo-information data are still very inadequate. In this study, a novel digital watermarking algorithm based on the scale-space feature points is applied to the remote sensing images, and the robustness of the embedded digital watermark and the impact on satellite image quality are evaluated and analysed. This kind of feature points are commonly invariant to Image rotation, scaling and translation, therefore they naturally fit into the requirement of geometrically robust image watermarking. The experiment results show almost all extracted watermarks have high values of normal correlation and can be recognized clearly after the processing of image compression, brightness adjustment and contrast adjustment. In addition, most of the extracted watermarks are identified after the geometric attacks. Furthermore, the unsupervised image classification is implemented on the watermarked images to evaluate the image quality reduction and the results show that classification accuracy is affected slightly after embedding watermarks into the satellite images.

  18. Modeling the statistics of image features and associated text

    NASA Astrophysics Data System (ADS)

    Barnard, Kobus; Duygulu, Pinar; Forsyth, David A.

    2001-12-01

    We present a methodology for modeling the statistics of image features and associated text in large datasets. The models used also serve to cluster the images, as images are modeled as being produced by sampling from a limited number of combinations of mixing components. Furthermore, because our approach models the joint occurrence image features and associated text, it can be used to predict the occurrence of either, based on observations or queries. This supports an attractive approach to image search as well as novel applications such a suggesting illustrations for blocks of text (auto-illustrate) and generating words for images outside the training set (auto-annotate). In this paper we illustrate the approach on 10,000 images of work from the Fine Arts Museum of San Francisco. The images include line drawings, paintings, and pictures of sculpture and ceramics. Many of the images have associated free text whose nature varies greatly, from physical description to interpretation and mood. We incorporate statistical natural language processing in order to deal with free text. We use WordNet to provide semantic grouping information and to help disambiguate word senses, as well as emphasize the hierarchical nature of semantic relationships.

  19. Improved image retrieval based on fuzzy colour feature vector

    NASA Astrophysics Data System (ADS)

    Ben-Ahmeida, Ahlam M.; Ben Sasi, Ahmed Y.

    2013-03-01

    One of Image indexing techniques is the Content-Based Image Retrieval which is an efficient way for retrieving images from the image database automatically based on their visual contents such as colour, texture, and shape. In this paper will be discuss how using content-based image retrieval (CBIR) method by colour feature extraction and similarity checking. By dividing the query image and all images in the database into pieces and extract the features of each part separately and comparing the corresponding portions in order to increase the accuracy in the retrieval. The proposed approach is based on the use of fuzzy sets, to overcome the problem of curse of dimensionality. The contribution of colour of each pixel is associated to all the bins in the histogram using fuzzy-set membership functions. As a result, the Fuzzy Colour Histogram (FCH), outperformed the Conventional Colour Histogram (CCH) in image retrieving, due to its speedy results, where were images represented as signatures that took less size of memory, depending on the number of divisions. The results also showed that FCH is less sensitive and more robust to brightness changes than the CCH with better retrieval recall values.

  20. Feature detection in satellite images using neural network technology

    NASA Technical Reports Server (NTRS)

    Augusteijn, Marijke F.; Dimalanta, Arturo S.

    1992-01-01

    A feasibility study of automated classification of satellite images is described. Satellite images were characterized by the textures they contain. In particular, the detection of cloud textures was investigated. The method of second-order gray level statistics, using co-occurrence matrices, was applied to extract feature vectors from image segments. Neural network technology was employed to classify these feature vectors. The cascade-correlation architecture was successfully used as a classifier. The use of a Kohonen network was also investigated but this architecture could not reliably classify the feature vectors due to the complicated structure of the classification problem. The best results were obtained when data from different spectral bands were fused.

  1. The neural representation of typical and atypical experiences of negative images: comparing fear, disgust and morbid fascination.

    PubMed

    Oosterwijk, Suzanne; Lindquist, Kristen A; Adebayo, Morenikeji; Barrett, Lisa Feldman

    2016-01-01

    Negative stimuli do not only evoke fear or disgust, but can also evoke a state of 'morbid fascination' which is an urge to approach and explore a negative stimulus. In the present neuroimaging study, we applied an innovative method to investigate the neural systems involved in typical and atypical conceptualizations of negative images. Participants received false feedback labeling their mental experience as fear, disgust or morbid fascination. This manipulation was successful; participants judged the false feedback correct for 70% of the trials on average. The neuroimaging results demonstrated differential activity within regions in the 'neural reference space for discrete emotion' depending on the type of feedback. We found robust differences in the ventrolateral prefrontal cortex, the dorsomedial prefrontal cortex and the lateral orbitofrontal cortex comparing morbid fascination to control feedback. More subtle differences in the dorsomedial prefrontal cortex and the lateral orbitofrontal cortex were also found between morbid fascination feedback and the other emotion feedback conditions. This study is the first to forward evidence about the neural representation of the experimentally unexplored state of morbid fascination. In line with a constructionist framework, our findings suggest that neural resources associated with the process of conceptualization contribute to the neural representation of this state. PMID:26180088

  2. Volumetric feature extraction and visualization of tomographic molecular imaging.

    PubMed

    Bajaj, Chandrajit; Yu, Zeyun; Auer, Manfred

    2003-01-01

    Electron tomography is useful for studying large macromolecular complex within their cellular context. The associate problems include crowding and complexity. Data exploration and 3D visualization of complexes require rendering of tomograms as well as extraction of all features of interest. We present algorithms for fully automatic boundary segmentation and skeletonization, and demonstrate their applications in feature extraction and visualization of cell and molecular tomographic imaging. We also introduce an interactive volumetric exploration and visualization tool (Volume Rover), which encapsulates implementations of the above volumetric image processing algorithms, and additionally uses efficient multi-resolution interactive geometry and volume rendering techniques for interactive visualization. PMID:14643216

  3. Investigation of image feature extraction by a genetic algorithm

    NASA Astrophysics Data System (ADS)

    Brumby, Steven P.; Theiler, James P.; Perkins, Simon J.; Harvey, Neal R.; Szymanski, John J.; Bloch, Jeffrey J.; Mitchell, Melanie

    1999-11-01

    We describe the implementation and performance of a genetic algorithm which generates image feature extraction algorithms for remote sensing applications. We describe our basis set of primitive image operators and present our chromosomal representation of a complete algorithm. Our initial application has been geospatial feature extraction using publicly available multi-spectral aerial-photography data sets. We present the preliminary results of our analysis of the efficiency of the classic genetic operations of crossover and mutation for our application, and discuss our choice of evolutionary control parameters. We exhibit some of our evolved algorithms, and discuss possible avenues for future progress.

  4. Hyperspectral image classifier based on beach spectral feature

    NASA Astrophysics Data System (ADS)

    Liang, Zhang; Lianru, Gao; Bing, Zhang

    2014-03-01

    The seashore, especially coral bank, is sensitive to human activities and environmental changes. A multispectral image, with coarse spectral resolution, is inadaptable for identify subtle spectral distinctions between various beaches. To the contrary, hyperspectral image with narrow and consecutive channels increases our capability to retrieve minor spectral features which is suit for identification and classification of surface materials on the shore. Herein, this paper used airborne hyperspectral data, in addition to ground spectral data to study the beaches in Qingdao. The image data first went through image pretreatment to deal with the disturbance of noise, radiation inconsistence and distortion. In succession, the reflection spectrum, the derivative spectrum and the spectral absorption features of the beach surface were inspected in search of diagnostic features. Hence, spectra indices specific for the unique environment of seashore were developed. According to expert decisions based on image spectrums, the beaches are ultimately classified into sand beach, rock beach, vegetation beach, mud beach, bare land and water. In situ surveying reflection spectrum from GER1500 field spectrometer validated the classification production. In conclusion, the classification approach under expert decision based on feature spectrum is proved to be feasible for beaches.

  5. Dermoscopy analysis of RGB-images based on comparative features

    NASA Astrophysics Data System (ADS)

    Myakinin, Oleg O.; Zakharov, Valery P.; Bratchenko, Ivan A.; Artemyev, Dmitry N.; Neretin, Evgeny Y.; Kozlov, Sergey V.

    2015-09-01

    In this paper, we propose an algorithm for color and texture analysis for dermoscopic images of human skin based on Haar wavelets, Local Binary Patterns (LBP) and Histogram Analysis. This approach is a modification of «7-point checklist» clinical method. Thus, that is an "absolute" diagnostic method because one is using only features extracted from tumor's ROI (Region of Interest), which can be selected manually and/or using a special algorithm. We propose additional features extracted from the same image for comparative analysis of tumor and healthy skin. We used Euclidean distance, Cosine similarity, and Tanimoto coefficient as comparison metrics between color and texture features extracted from tumor's and healthy skin's ROI separately. A classifier for separating melanoma images from other tumors has been built by SVM (Support Vector Machine) algorithm. Classification's errors with and without comparative features between skin and tumor have been analyzed. Significant increase of recognition quality with comparative features has been demonstrated. Moreover, we analyzed two modes (manual and automatic) for ROI selecting on tumor and healthy skin areas. We have reached 91% of sensitivity using comparative features in contrast with 77% of sensitivity using the only "absolute" method. The specificity was the invariable (94%) in both cases.

  6. Atypical Trigeminal Neuralgia Secondary to Meningioma

    PubMed Central

    Niwant, Premeshwar; Motwani, Mukta; Naik, Sushil

    2015-01-01

    Trigeminal neuralgia is a disorder of the fifth cranial nerve that causes episodes of intense, stabbing, electric shock-like pain that lasts from few seconds to few minutes in the areas of the face where the branches of the nerve are distributed. More than one nerve branch can be affected by the disorder. We report an unusual case of trigeminal neuralgia affecting right side of face presenting atypical features of neuralgia and not responding to the usual course of treatment. The magnetic resonance imaging study of brain revealed a large extra-axial mass involving right cerebellopontine angle region causing moderate pressure effect on trigeminal nerve and brain stem. The aim of this case report is to show a tumor of cerebellopontine angle, presenting clinically as atypical trigeminal neuralgia. PMID:26664753

  7. Atypical Trigeminal Neuralgia Secondary to Meningioma.

    PubMed

    Niwant, Premeshwar; Motwani, Mukta; Naik, Sushil

    2015-01-01

    Trigeminal neuralgia is a disorder of the fifth cranial nerve that causes episodes of intense, stabbing, electric shock-like pain that lasts from few seconds to few minutes in the areas of the face where the branches of the nerve are distributed. More than one nerve branch can be affected by the disorder. We report an unusual case of trigeminal neuralgia affecting right side of face presenting atypical features of neuralgia and not responding to the usual course of treatment. The magnetic resonance imaging study of brain revealed a large extra-axial mass involving right cerebellopontine angle region causing moderate pressure effect on trigeminal nerve and brain stem. The aim of this case report is to show a tumor of cerebellopontine angle, presenting clinically as atypical trigeminal neuralgia. PMID:26664753

  8. The fuzzy Hough Transform-feature extraction in medical images

    SciTech Connect

    Philip, K.P.; Dove, E.L.; Stanford, W.; Chandran, K.B. ); McPherson, D.D.; Gotteiner, N.L. . Dept. of Internal Medicine)

    1994-06-01

    Identification of anatomical features is a necessary step for medical image analysis. Automatic methods for feature identification using conventional pattern recognition techniques typically classify an object as a member of a predefined class of objects, but do not attempt to recover the exact or approximate shape of that object. For this reason, such techniques are usually not sufficient to identify the borders of organs when individual geometry varies in local detail, even though the general geometrical shape is similar. The authors present an algorithm that detects features in an image based on approximate geometrical models. The algorithm is based on the traditional and generalized Hough Transforms but includes notions from fuzzy set theory. The authors use the new algorithm to roughly estimate the actual locations of boundaries of an internal organ, and from this estimate, to determine a region of interest around the organ. Based on this rough estimate of the border location, and the derived region of interest, the authors find the final estimate of the true borders with other image processing techniques. The authors present results that demonstrate that the algorithm was successfully used to estimate the approximate location of the chest wall in humans, and of the left ventricular contours of a dog heart obtained from cine-computed tomographic images. The authors use this fuzzy Hough Transform algorithm as part of a larger procedures to automatically identify the myocardial contours of the heart. This algorithm may also allow for more rapid image processing and clinical decision making in other medical imaging applications.

  9. Radiological Features of Hepatocellular Carcinoma

    PubMed Central

    Shah, Samir; Shukla, Akash; Paunipagar, Bhawan

    2014-01-01

    Present article is a review of radiological features of hepatocellular carcinoma on various imaging modalities. With the advancement in imaging techniques, biopsy is rarely needed for diagnosis of hepatocellular carcinoma (HCC), unlike other malignancies. Imaging is useful not only for diagnosis but also for surveillance, therapy and assessing response to treatment. The classical and the atypical radiological features of HCC have been described. PMID:25755613

  10. Investigation of efficient features for image recognition by neural networks.

    PubMed

    Goltsev, Alexander; Gritsenko, Vladimir

    2012-04-01

    In the paper, effective and simple features for image recognition (named LiRA-features) are investigated in the task of handwritten digit recognition. Two neural network classifiers are considered-a modified 3-layer perceptron LiRA and a modular assembly neural network. A method of feature selection is proposed that analyses connection weights formed in the preliminary learning process of a neural network classifier. In the experiments using the MNIST database of handwritten digits, the feature selection procedure allows reduction of feature number (from 60 000 to 7000) preserving comparable recognition capability while accelerating computations. Experimental comparison between the LiRA perceptron and the modular assembly neural network is accomplished, which shows that recognition capability of the modular assembly neural network is somewhat better. PMID:22391231

  11. Texture Features from Mammographic Images and Risk of Breast Cancer

    PubMed Central

    Manduca, Armando; Carston, Michael J.; Heine, John J.; Scott, Christopher G.; Pankratz, V. Shane; Brandt, Kathy R.; Sellers, Thomas A.; Vachon, Celine M.; Cerhan, James R.

    2009-01-01

    Mammographic percent density (PD) is a strong risk factor for breast cancer, but there has been relatively little systematic evaluation of other features in mammographic images that might additionally predict breast cancer risk. We evaluated the association of a large number of image texture features with risk of breast cancer using a clinic-based case-control study of digitized film mammograms, all with screening mammograms prior to breast cancer diagnosis. The sample was split into training (123 cases, 258 controls) and validation (123 cases, 264 controls) datasets. Age and body mass index (BMI)-adjusted Odds Ratios (ORs) per standard deviation change in the feature, 95% confidence intervals, and the area under the receiver operator characteristic curve (AUC) were obtained using logistic regression. A bootstrap approach was used to identify the strongest features in the training dataset, and results for features that validated in the second half of the sample were reported using the full dataset. The mean age at mammography was 64.0 ± 10.2 years, and the mean time from mammography to breast cancer was 3.7 ± 1.0 (range 2.0-5.9 years). PD was associated with breast cancer risk (OR=1.49; 1.25-1.78). The strongest features that validated from each of several classes (Markovian, run-length, Laws, wavelet and Fourier) showed similar ORs as PD and predicted breast cancer at a similar magnitude (AUC=0.58-0.60) as PD (AUC=0.58). All of these features were automatically calculated (unlike PD), and measure texture at a coarse scale. These features were moderately correlated with PD (r = 0.39-0.64), and after adjustment for PD, each of the features attenuated only slightly and retained statistical significance. However, simultaneous inclusion of these features in a model with PD did not significantly improve the ability to predict breast cancer. PMID:19258482

  12. Recognition and diagnosis of atypical depression.

    PubMed

    Thase, Michael E

    2007-01-01

    The term atypical depression dates to the first wave of reports describing differential response to monoamine oxidase inhibitors (MAOIs) and tricyclic antidepressants (TCAs). In contrast to more TCA-responsive depressions, patients with so-called atypical symptoms (e.g., hypersomnia, interpersonal sensitivity, leaden paralysis, increased appetite and/or weight, and phobic anxiety) were observed to be more responsive to MAOIs. After several decades of controversy and debate, the phrase "with atypical features" was added as an episode specifier in the DSM-IV in 1994. The 1-year prevalence of the defined atypical depression subtype is approximately 1% to 4%; around 15% to 29% of patients with major depressive disorder have atypical depression. Hardly "atypical" in contemporary contexts, atypical depression also is common in dysthymic bipolar II disorders and is notable for its early age at onset, more chronic course, and high rates of comorbidity with social phobia and panic disorder with agoraphobia. The requirement of preserved mood reactivity is arguably the most controversial of the DSM-IV criteria for atypical depression. When compared with melancholia, the neurobiological profiles of patients with atypical depression are relatively normal. The utility of the atypical depression subtype for differential therapeutics diminished substantially when the TCAs were supplanted as first-line antidepressants by the selective serotonin reuptake inhibitors. Although introduction of safer MAOIs has fostered renewed interest in atypical depression, the validity and importance of the DSM-IV definition of atypical depression for the nosology of affective illness remains an open question. PMID:17640153

  13. Image enhancement techniques applied to solar feature detection

    NASA Astrophysics Data System (ADS)

    Kowalski, Artur J.

    This dissertation presents the development of automatic image enhancement techniques for solar feature detection. The new method allows for detection and tracking of the evolution of filaments in solar images. Series of H-alpha full-disk images are taken in regular time intervals to observe the changes of the solar disk features. In each picture, the solar chromosphere filaments are identified for further evolution examination. The initial preprocessing step involves local thresholding to convert grayscale images into black-and-white pictures with chromosphere granularity enhanced. An alternative preprocessing method, based on image normalization and global thresholding is presented. The next step employs morphological closing operations with multi-directional linear structuring elements to extract elongated shapes in the image. After logical union of directional filtering results, the remaining noise is removed from the final outcome using morphological dilation and erosion with a circular structuring element. Experimental results show that the developed techniques can achieve excellent results in detecting large filaments and good detection rates for small filaments. The final chapter discusses proposed directions of the future research and applications to other areas of solar image processing, in particular to detection of solar flares, plages and sunspots.

  14. Characterizing mammographic images by using generic texture features

    PubMed Central

    2012-01-01

    Introduction Although mammographic density is an established risk factor for breast cancer, its use is limited in clinical practice because of a lack of automated and standardized measurement methods. The aims of this study were to evaluate a variety of automated texture features in mammograms as risk factors for breast cancer and to compare them with the percentage mammographic density (PMD) by using a case-control study design. Methods A case-control study including 864 cases and 418 controls was analyzed automatically. Four hundred seventy features were explored as possible risk factors for breast cancer. These included statistical features, moment-based features, spectral-energy features, and form-based features. An elaborate variable selection process using logistic regression analyses was performed to identify those features that were associated with case-control status. In addition, PMD was assessed and included in the regression model. Results Of the 470 image-analysis features explored, 46 remained in the final logistic regression model. An area under the curve of 0.79, with an odds ratio per standard deviation change of 2.88 (95% CI, 2.28 to 3.65), was obtained with validation data. Adding the PMD did not improve the final model. Conclusions Using texture features to predict the risk of breast cancer appears feasible. PMD did not show any additional value in this study. With regard to the features assessed, most of the analysis tools appeared to reflect mammographic density, although some features did not correlate with PMD. It remains to be investigated in larger case-control studies whether these features can contribute to increased prediction accuracy. PMID:22490545

  15. Detection of fungal damaged popcorn using image property covariance features

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Covariance-matrix-based features were applied to the detection of popcorn infected by a fungus that cause a symptom called “blue-eye.” This infection of popcorn kernels causes economic losses because of their poor appearance and the frequently disagreeable flavor of the popped kernels. Images of ker...

  16. Identification and Quantification Soil Redoximorphic Features by Digital Image Processing

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Soil redoximorphic features (SRFs) have provided scientists and land managers with insight into relative soil moisture for approximately 60 years. The overall objective of this study was to develop a new method of SRF identification and quantification from soil cores using a digital camera and imag...

  17. Feature-based multiexposure image-sequence fusion with guided filter and image alignment

    NASA Astrophysics Data System (ADS)

    Xu, Liang; Du, Junping; Zhang, Zhenhong

    2015-01-01

    Multiexposure fusion images have a higher dynamic range and reveal more details than a single captured image of a real-world scene. A clear and intuitive feature-based fusion technique for multiexposure image sequences is conceptually proposed. The main idea of the proposed method is to combine three image features [phase congruency (PC), local contrast, and color saturation] to obtain weight maps of the images. Then, the weight maps are further refined using a guided filter which can improve their accuracy. The final fusion result is constructed using the weighted sum of the source image sequence. In addition, for multiexposure image-sequence fusion involving dynamic scenes containing moving objects, ghost artifacts can easily occur if fusion is directly performed. Therefore, an image-alignment method is first used to adjust the input images to correspond to a reference image, after which fusion is performed. Experimental results demonstrate that the proposed method has a superior performance compared to the existing methods.

  18. Diffusion tensor image registration using tensor geometry and orientation features.

    PubMed

    Yang, Jinzhong; Shen, Dinggang; Davatzikos, Christos; Verma, Ragini

    2008-01-01

    This paper presents a method for deformable registration of diffusion tensor (DT) images that integrates geometry and orientation features into a hierarchical matching framework. The geometric feature is derived from the structural geometry of diffusion and characterizes the shape of the tensor in terms of prolateness, oblateness, and sphericity of the tensor. Local spatial distributions of the prolate, oblate, and spherical geometry are used to create an attribute vector of geometric feature for matching. The orientation feature improves the matching of the WM fiber tracts by taking into account the statistical information of underlying fiber orientations. These features are incorporated into a hierarchical deformable registration framework to develop a diffusion tensor image registration algorithm. Extensive experiments on simulated and real brain DT data establish the superiority of this algorithm for deformable matching of diffusion tensors, thereby aiding in atlas creation. The robustness of the method makes it potentially useful for group-based analysis of DT images acquired in large studies to identify disease-induced and developmental changes. PMID:18982691

  19. Feature extraction from mammographic images using fast marching methods

    NASA Astrophysics Data System (ADS)

    Bottigli, U.; Golosio, B.

    2002-07-01

    Features extraction from medical images represents a fundamental step for shape recognition and diagnostic support. The present work faces the problem of the detection of large features, such as massive lesions and organ contours, from mammographic images. The regions of interest are often characterized by an average grayness intensity that is different from the surrounding. In most cases, however, the desired features cannot be extracted by simple gray level thresholding, because of image noise and non-uniform density of the surrounding tissue. In this work, edge detection is achieved through the fast marching method (Level Set Methods and Fast Marching Methods, Cambridge University Press, Cambridge, 1999), which is based on the theory of interface evolution. Starting from a seed point in the shape of interest, a front is generated which evolves according to an appropriate speed function. Such function is expressed in terms of geometric properties of the evolving interface and of image properties, and should become zero when the front reaches the desired boundary. Some examples of application of such method to mammographic images from the CALMA database (Nucl. Instr. and Meth. A 460 (2001) 107) are presented here and discussed.

  20. Image Recognition and Feature Detection in Solar Physics

    NASA Astrophysics Data System (ADS)

    Martens, Petrus C.

    2012-05-01

    The Solar Dynamics Observatory (SDO) data repository will dwarf the archives of all previous solar physics missions put together. NASA recognized early on that the traditional methods of analyzing the data -- solar scientists and grad students in particular analyzing the images by hand -- would simply not work and tasked our Feature Finding Team (FFT) with developing automated feature recognition modules for solar events and phenomena likely to be observed by SDO. Having these metadata available on-line will enable solar scientist to conduct statistical studies involving large sets of events that would be impossible now with traditional means. We have followed a two-track approach in our project: we have been developing some existing task-specific solar feature finding modules to be "pipe-line" ready for the stream of SDO data, plus we are designing a few new modules. Secondly, we took it upon us to develop an entirely new "trainable" module that would be capable of identifying different types of solar phenomena starting from a limited number of user-provided examples. Both approaches are now reaching fruition, and I will show examples and movies with results from several of our feature finding modules. In the second part of my presentation I will focus on our “trainable” module, which is the most innovative in character. First, there is the strong similarity between solar and medical X-ray images with regard to their texture, which has allowed us to apply some advances made in medical image recognition. Second, we have found that there is a strong similarity between the way our trainable module works and the way our brain recognizes images. The brain can quickly recognize similar images from key characteristics, just as our code does. We conclude from that that our approach represents the beginning of a more human-like procedure for computer image recognition.

  1. Evaluation of Selected Features for CAR Detection in Aerial Images

    NASA Astrophysics Data System (ADS)

    Tuermer, S.; Leitloff, J.; Reinartz, P.; Stilla, U.

    2011-09-01

    The extraction of vehicles from aerial images provides a wide area traffic situation within a short time. Applications for the gathered data are various and reach from smart routing in the case of congestions to usability validation of roads in the case of disasters. The challenge of the vehicle detection task is finding adequate features which are capable to separate cars from other objects; especially those that look similar. We present an experiment where selected features show their ability of car detection. Precisely, Haar-like and HoG features are utilized and passed to the AdaBoost algorithm for calculating the final detector. Afterwards the classifying power of the features is accurately analyzed and evaluated. The tests a carried out on aerial data from the inner city of Munich, Germany and include small inner city roads with rooftops close by which raise the complexity factor.

  2. Assessment of femur geometrical parameters using EOS™ imaging technology in patients with atypical femur fractures; preliminary results.

    PubMed

    Morin, Suzanne N; Wall, Michelle; Belzile, Etienne L; Godbout, Benoit; Moser, Thomas P; Michou, Laëtitia; Ste-Marie, Louis-Georges; de Guise, Jacques A; Rahme, Elham; Brown, Jacques P

    2016-02-01

    Atypical femur fractures (AFF) arise in the subtrochanteric and diaphyseal regions. Because of this unique distribution, we hypothesized that patients with AFF demonstrate specific geometrical variations of their lower limb whereby baseline tensile forces applied to the lateral cortex are higher and might favor the appearance of these rare stress fractures, when exposed to bisphosphonates. Using the low irradiation 2D-3D X-ray scanner EOS™ imaging technology we aimed to characterize and compare femur geometric parameters between women who sustained bisphosphonate-associated AFF and those who had experienced similar duration of exposure to bisphosphonates but did not sustain fractures. Conditional logistic regression models were constructed to estimate the association between selected geometric parameters and the occurrence of AFF. We identified 16 Caucasian women with AFF and recruited 16 ethnicity-, sex-, age-, height- and cumulative bisphosphonate exposure-matched controls from local osteoporosis clinics. Compared to controls, those with AFF had more lateral femur bowing (-3.2° SD [3.4] versus -0.8° SD [1.9] p=0.02). In regression analysis, lateral femur bowing was associated with the risk of AFF (aOR 1.54; 95% CI 1.04-2.28, p=0.03). Women who sustained a subtrochanteric AFF demonstrated a lesser femoral neck shaft angle (varus geometry) than those with a fracture at a diaphyseal site (121.9 [3.6]° versus 127.6 [7.2]°, p=0.07), whereas femur bowing was more prominent in those with a diaphyseal fracture compared to those with a subtrochanteric fracture (-4.3 [3.2]° versus -0.9 [2.7]°, p=0.07). Our analyses support that subjects with AFF exhibit femoral geometry parameters that result in higher tensile mechanical load on the lateral femur. This may play a critical role in the pathogenesis of AFF and requires further evaluation in a larger size population. PMID:26541215

  3. Image recognition of diseased rice seeds based on color feature

    NASA Astrophysics Data System (ADS)

    Cheng, Fang; Ying, Yibin

    2004-11-01

    The objective of this research is to develop a digital image analysis algorithm for detection of diseased rice seeds based on color features. The rice seeds used for this study involved five varieties of Jinyou402, Shanyou10, Zhongyou207, Jiayou99 and IIyou3207. Images of rice seeds were acquired with a color machine vision system. Each original RGB image was converted to HSV color space and preprocessed to show, as hue in the seed region while the pixels value of background was zero. The hue values were scaled so that they varied from 0.0 to 1.0. Then six color features were extracted and evaluated for their contributions to seed classification. Determined using Blocks method, the mean hue value shows the strongest classification ability. Parzen windowing function method was used to estimate probability density distribution and a threshold of mean hue was drawn to classify normal seeds and diseased seeds. The average accuracy of test data set is 95% for Jinyou402. Then the feature of hue histogram was extracted for diseased seeds and partitioned into two clusters of spot diseased seeds and severe diseased seeds. Desired results were achieved when the two cancroids locations were used to discriminate the disease degree. Combined with the two features of mean hue and histogram, all seeds could be classified as normal seeds, spot diseased seeds and severe diseased seeds. Finally, the algorithm was implemented for all the five varieties to test the adaptability.

  4. Quantitative imaging features to predict cancer status in lung nodules

    NASA Astrophysics Data System (ADS)

    Liu, Ying; Balagurunathan, Yoganand; Atwater, Thomas; Antic, Sanja; Li, Qian; Walker, Ronald; Smith, Gary T.; Massion, Pierre P.; Schabath, Matthew B.; Gillies, Robert J.

    2016-03-01

    Background: We propose a systematic methodology to quantify incidentally identified lung nodules based on observed radiological traits on a point scale. These quantitative traits classification model was used to predict cancer status. Materials and Methods: We used 102 patients' low dose computed tomography (LDCT) images for this study, 24 semantic traits were systematically scored from each image. We built a machine learning classifier in cross validation setting to find best predictive imaging features to differentiate malignant from benign lung nodules. Results: The best feature triplet to discriminate malignancy was based on long axis, concavity and lymphadenopathy with average AUC of 0.897 (Accuracy of 76.8%, Sensitivity of 64.3%, Specificity of 90%). A similar semantic triplet optimized on Sensitivity/Specificity (Youden's J index) included long axis, vascular convergence and lymphadenopathy which had an average AUC of 0.875 (Accuracy of 81.7%, Sensitivity of 76.2%, Specificity of 95%). Conclusions: Quantitative radiological image traits can differentiate malignant from benign lung nodules. These semantic features along with size measurement enhance the prediction accuracy.

  5. Feature-aided multiple target tracking in the image plane

    NASA Astrophysics Data System (ADS)

    Brown, Andrew P.; Sullivan, Kevin J.; Miller, David J.

    2006-05-01

    Vast quantities of EO and IR data are collected on airborne platforms (manned and unmanned) and terrestrial platforms (including fixed installations, e.g., at street intersections), and can be exploited to aid in the global war on terrorism. However, intelligent preprocessing is required to enable operator efficiency and to provide commanders with actionable target information. To this end, we have developed an image plane tracker which automatically detects and tracks multiple targets in image sequences using both motion and feature information. The effects of platform and camera motion are compensated via image registration, and a novel change detection algorithm is applied for accurate moving target detection. The contiguous pixel blob on each moving target is segmented for use in target feature extraction and model learning. Feature-based target location measurements are used for tracking through move-stop-move maneuvers, close target spacing, and occlusion. Effective clutter suppression is achieved using joint probabilistic data association (JPDA), and confirmed target tracks are indicated for further processing or operator review. In this paper we describe the algorithms implemented in the image plane tracker and present performance results obtained with video clips from the DARPA VIVID program data collection and from a miniature unmanned aerial vehicle (UAV) flight.

  6. [Atypical odontalgia].

    PubMed

    Türp, Jens Christoph

    2005-01-01

    In spite of its first description by the English surgeon JOHN HUNTER more than 200 years ago, atypical odontalgia (AO), or phantom tooth pain, is not universally known among dentists. AO is a persistent neuropathic pain which may be initiated after deafferentiation of trigeminal nerve fibers following root canal treatment, apicectomy, or tooth extraction. In the absence of pathological clinical or radiological findings, the diagnosis is made by exclusion. After a thorough patient education about the condition, pharmacological and psychological pain management is required. Invasive and irreversible treatment attempts are contraindicated. PMID:16342640

  7. Atypical Inflammasomes.

    PubMed

    Janowski, Ann M; Sutterwala, Fayyaz S

    2016-01-01

    Pattern recognition receptors, including members of the NLR and PYHIN families, are essential for recognition of both pathogen- and host-derived danger signals. A number of molecules in these families are capable of forming multiprotein complexes termed inflammasomes that result in the activation of caspase-1. In addition to NLRP1, NLRP3, NLRC4, and AIM2, which form well-described inflammasome complexes, IFI16, NLRP6, NLRP7, NLRP12, and NLRC5 have also been proposed to form inflammasomes under specific conditions. The structure and function of these atypical inflammasomes will be highlighted here. PMID:27221480

  8. Deep Optical Images of Malin 1 Reveal New Features

    NASA Astrophysics Data System (ADS)

    Galaz, Gaspar; Milovic, Carlos; Suc, Vincent; Busta, Luis; Lizana, Guadalupe; Infante, Leopoldo; Royo, Santiago

    2015-12-01

    We present Megacam deep optical images (g and r) of Malin 1 obtained with the 6.5 m Magellan/Clay telescope, detecting structures down to ˜28 B mag arcsec-2. In order to enhance galaxy features buried in the noise, we use a noise reduction filter based on the total generalized variation regularizator. This method allows us to detect and resolve very faint morphological features, including spiral arms, with a high visual contrast. For the first time, we can appreciate an optical image of Malin 1 and its morphology in full view. The images provide unprecedented detail, compared to those obtained in the past with photographic plates and CCD, including Hubble Space Telescope imaging. We detect two peculiar features in the disk/spiral arms. The analysis suggests that the first one is possibly a background galaxy, and the second is an apparent stream without a clear nature, but could be related to the claimed past interaction between Malin 1 and the galaxy SDSSJ123708.91+142253.2. Malin 1 exhibits features suggesting the presence of stellar associations and clumps of molecular gas, not seen before with such a clarity. Using these images, we obtain a diameter for Malin 1 of 160 kpc, ˜50 kpc larger than previous estimates. A simple analysis shows that the observed spiral arms reach very low luminosity and mass surface densities, to levels much lower than the corresponding values for the Milky Way. This paper includes data gathered with the 6.5 meter Magellan Telescopes located at Las Campanas Observatory, Chile.

  9. Characteristic imaging features of body packers: a pictorial essay.

    PubMed

    Ab Hamid, Suzana; Abd Rashid, Saiful Nizam; Mohd Saini, Suraini

    2012-06-01

    The drug-trafficking business has risen tremendously because of the current increased demand for illegal narcotics. The smugglers conceal the drugs in their bodies (body packers) in order to bypass the tight security at international borders. A suspected body packer will normally be sent to the hospital for imaging investigations to confirm the presence of drugs in the body. Radiologists, therefore, need to be familiar with and able to identify drug packets within the human body because they shoulder the legal responsibilities. This pictorial essay describes the characteristic imaging features of drug packets within the gastrointestinal tract. PMID:22415809

  10. Imaging features of benign and malignant ampullary and periampullary lesions.

    PubMed

    Nikolaidis, Paul; Hammond, Nancy A; Day, Kevin; Yaghmai, Vahid; Wood, Cecil G; Mosbach, David S; Harmath, Carla B; Taffel, Myles T; Horowitz, Jeanne M; Berggruen, Senta M; Miller, Frank H

    2014-01-01

    The ampulla of Vater is an important anatomic landmark where the common bile duct and main pancreatic duct converge in the major duodenal papilla. Imaging evaluation of the ampulla and periampullary region poses a unique diagnostic challenge to radiologists because of the region's complex and variable anatomy and the variety of lesions that can occur. Lesions intrinsic to the ampulla and involved segment of the biliary tree can be neoplastic, inflammatory, or congenital. Neoplastic lesions include ampullary adenocarcinomas and adenomas, which often are difficult to differentiate, as well as pancreatic or duodenal adenocarcinomas, pancreatic neuroendocrine tumors, and cholangiocarcinomas. Ultrasonography (US), computed tomography, magnetic resonance (MR) imaging, and MR cholangiopancreatography are commonly used to evaluate this region. Endoscopic retrograde cholangiopancreatography or endoscopic US examination may be necessary for more definitive evaluation. Periampullary conditions in the duodenum that may secondarily involve the ampulla include neoplasms, duodenitis, duodenal diverticula, and Brunner's gland hyperplasia or hamartomas. Because these lesions can exhibit a wide overlap of imaging features and subtle or nonspecific imaging findings, diagnosis is made on the basis of patient age, clinical history, and imaging and laboratory findings. Given the complexity of imaging evaluation of the ampulla and periampullary region, it is essential for radiologists to understand the variety of lesions that can occur and recognize their imaging characteristics. PMID:24819785

  11. Adrenal imaging for adenoma characterization: imaging features, diagnostic accuracies and differential diagnoses.

    PubMed

    Park, Jung Jae; Park, Byung Kwan; Kim, Chan Kyo

    2016-06-01

    Adrenocortical adenoma is the most common adrenal tumour. This lesion is frequently encountered on cross-sectional imaging that has been performed for unrelated reasons. Adrenal adenoma manifests various imaging features on CT, MRI and positron emission tomography/CT. The learning objectives of this review are to describe the imaging findings of adrenocortical adenoma, to compare the sensitivities of different imaging modalities for adenoma characterization and to introduce differential diagnoses. PMID:26867466

  12. Feature-based eye corner detection from static images

    NASA Astrophysics Data System (ADS)

    Xia, Haiying; Yan, Guoping; You, Chao

    2009-10-01

    Eye corner detection is important for eye extraction, face normalization, other facial landmark extraction and so on. We present a feature-based method for eye corner detection from static images in this paper. This method is capable of locating eye corners automatically. The process of eye corner detection is divided into two stages: classifier training and classifier application. For training, two classifiers trained by AdaBoost with Haar-like features, are skillfully designed to detect inner eye corners and outer eye corners. Then, two classifiers are applied to input images to search targets. Eye corners are finally located according to two eye models from targets. Experimental results tested on BioID face database and our own database demonstrate that our method obtains a high accuracy under clutter conditions.

  13. Comparison of Magnetic Resonance Imaging Findings between Pathologically Proven Cases of Atypical Tubercular Spine and Tumour Metastasis: A Retrospective Study in 40 Patients

    PubMed Central

    Khalid, Mohd; Sabir, Aamir Bin; Khalid, Saifullah

    2016-01-01

    Study Design Retrospective study. Purpose To note the magnetic resonance imaging (MRI) differences between pathologically proven cases of atypical spinal tuberculosis and spinal metastasis in 40 cases. Overview of Literature Spinal tuberculosis, or Pott's spine, constitutes less than 1% of all cases of tuberculosis and can be associated with a neurologic deficit. Breast, prostate and lung cancer are responsible for more than 80% of metastatic bone disease cases, and spine is the most common site of bone metastasis. Thus, early diagnosis and prompt management of these pathologies are essential in preventing various complications. Methods We retrospectively reviewed 40 cases of atypical tuberculosis and metastasis affecting the spine from the year 2012 to 2014, with 20 cases each that were proven by histopathological examination. MR imaging was performed on 1.5 T MR-Scanner (Magnetom Avanto, Siemens) utilizing standard surface coils of spine with contrast injection. Chi-square test was used for determining the statistical significance and p-values were calculated. Results The most common site of involvement was the thoracic spine, seen in 85% cases of metastasis and 65% cases of Pott's spine (p=0.144). The mean age of patients with tubercular spine was found to be 40 years and that of metastatic spine was 56 years. The following MR imaging findings showed statistical significance (p<0.05): combined vertebral body and posterior elements involvement, skip lesions, solitary lesion, intra-spinal lesions, concentric collapse, abscess formation and syrinx formation. Conclusions Tuberculosis should be considered in the differential diagnosis of various spinal lesions including metastasis, fungal spondylodiskitis, sarcoidosis and lymphoma, particularly in endemic countries. Spinal tuberculosis is considered one of the great mimickers of disease as it could present in a variety of typical and atypical patterns, so proper imaging must be performed in order to facilitate

  14. Dual-pass feature extraction on human vessel images.

    PubMed

    Hernandez, W; Grimm, S; Andriantsimiavona, R

    2014-06-01

    We present a novel algorithm for the extraction of cavity features on images of human vessels. Fat deposits in the inner wall of such structure introduce artifacts, and regions in the images captured invalidating the usual assumption of an elliptical model which makes the process of extracting the central passage effectively more difficult. Our approach was designed to cope with these challenges and extract the required image features in a fully automated, accurate, and efficient way using two stages: the first allows to determine a bounding segmentation mask to prevent major leakages from pixels of the cavity area by using a circular region fill that operates as a paint brush followed by Principal Component Analysis with auto correction; the second allows to extract a precise cavity enclosure using a micro-dilation filter and an edge-walking scheme. The accuracy of the algorithm has been tested using 30 computed tomography angiography scans of the lower part of the body containing different degrees of inner wall distortion. The results were compared to manual annotations from a specialist resulting in sensitivity around 98 %, false positive rate around 8 %, and positive predictive value around 93 %. The average execution time was 24 and 18 ms on two types of commodity hardware over sections of 15 cm of length (approx. 1 ms per contour) which makes it more than suitable for use in interactive software applications. Reproducibility tests were also carried out with synthetic images showing no variation for the computed diameters against the theoretical measure. PMID:24197278

  15. Featured Image: A New Look at Malin 1

    NASA Astrophysics Data System (ADS)

    Kohler, Susanna

    2016-01-01

    Monochrome, inverted version of Malin 1. [Adapted from Galaz et al. 2015]The above image of Malin 1, the faintest and largest low-surface-brightness galaxy ever observed, was obtained with an instrument called Megacam on the 6.5m Magellan/Clay telescope. Gaspar Galaz (Pontifical Catholic University of Chile) and collaborators used Megacam to obtain deep optical observations of Malin 1. They then used novel noise-reduction and image-processing techniques to create this spectacular image of the spiral galaxy located roughly 1.2 billion light-years away. This new view of Malin 1 reveals details weve never before seen, including a stream within the disk that may have been caused by a past interaction between Malin 1 and another galaxy near it. Check outthe image to the rightfor a monochrome, inverted version thatmakes it a little easier to see some of Malin 1s features. To see the full original images and to learn more about what the images reveal about Malin 1, see the paper below.CitationGaspar Galaz et al 2015 ApJ 815 L29. doi:10.1088/2041-8205/815/2/L29

  16. The speckle image reconstruction of the solar small scale features

    NASA Astrophysics Data System (ADS)

    Zhong, Libo; Tian, Yu; Rao, Changhui

    2014-11-01

    The resolution of the astronomical object observed by the earth-based telescope is limited due to the atmospheric turbulence. Speckle image reconstruction method provides access to detect small-scale solar features near the diffraction limit of the telescope. This paper describes the implementation of the reconstruction of images obtained by the 1-m new vacuum solar telescope at Full-Shine solar observatory. Speckle masking method is used to reconstruct the Fourier phases for its better dynamic range and resolution capabilities. Except of the phase reconstruction process, several problems encounter in the solar image reconstruction are discussed. The details of the implement including the flat-field, image segmentation, Fried parameter estimation and noise filter estimating are described particularly. It is demonstrated that the speckle image reconstruction is effective to restore the wide field of view images. The qualities of the restorations are evaluated by the contrast ratio. When the Fried parameter is 10cm, the contrast ratio of the sunspot and granulation can be improved from 0.3916 to 0.6845 and from 0.0248 to 0.0756 respectively.

  17. Multispectral image feature fusion for detecting land mines

    SciTech Connect

    Clark, G.A.; Fields, D.J.; Sherwood, R.J.

    1994-11-15

    Our system fuses information contained in registered images from multiple sensors to reduce the effect of clutter and improve the the ability to detect surface and buried land mines. The sensor suite currently consists if a camera that acquires images in sixible wavelength bands, du, dual-band infrared (5 micron and 10 micron) and ground penetrating radar. Past research has shown that it is extremely difficult to distinguish land mines from background clutter in images obtained from a single sensor. It is hypothesized, however, that information fused from a suite of various sensors is likely to provide better detection reliability, because the suite of sensors detects a variety of physical properties that are more separate in feature space. The materials surrounding the mines can include natural materials (soil, rocks, foliage, water, holes made by animals and natural processes, etc.) and some artifacts.

  18. CFA-aware features for steganalysis of color images

    NASA Astrophysics Data System (ADS)

    Goljan, Miroslav; Fridrich, Jessica

    2015-03-01

    Color interpolation is a form of upsampling, which introduces constraints on the relationship between neighboring pixels in a color image. These constraints can be utilized to substantially boost the accuracy of steganography detectors. In this paper, we introduce a rich model formed by 3D co-occurrences of color noise residuals split according to the structure of the Bayer color filter array to further improve detection. Some color interpolation algorithms, AHD and PPG, impose pixel constraints so tight that extremely accurate detection becomes possible with merely eight features eliminating the need for model richification. We carry out experiments on non-adaptive LSB matching and the content-adaptive algorithm WOW on five different color interpolation algorithms. In contrast to grayscale images, in color images that exhibit traces of color interpolation the security of WOW is significantly lower and, depending on the interpolation algorithm, may even be lower than non-adaptive LSB matching.

  19. Spinal Neuroarthropathy: Pathophysiology, Clinical and Imaging Features, and Differential Diagnosis.

    PubMed

    Ledbetter, Luke N; Salzman, Karen L; Sanders, R Kent; Shah, Lubdha M

    2016-01-01

    Spinal neuroarthropathy (SNA), or Charcot spine, is a progressive destructive arthropathy occurring after loss of neuroprotective sensation and proprioceptive reflexes. Clinical diagnosis is difficult because of the variable length to presentation after initial neurologic damage and the limited symptoms given preexisting neurologic deficits. SNA is also a diagnostic challenge because its imaging features are similar to those of spinal conditions such as discitis-osteomyelitis, osseous tuberculosis, hemodialysis-related spondyloarthropathy, and pseudarthrosis. The most important imaging clues for diagnosis of SNA are involvement of both anterior and posterior elements at the thoracolumbar and lumbosacral junctions. Additional imaging clues include vacuum phenomenon within the disk (indicating excessive motion), malalignment, and paraspinal soft-tissue masses or fluid collections containing bone debris. Despite these imaging signs, findings may overlap in some cases with those of infection, or SNA can be superinfected, and biopsy may be necessary. Development of SNA requires a preexisting neurologic condition, most commonly traumatic spinal cord injury. Areas of greatest mobility and weight bearing within the desensate spine experience repetitive microtrauma and unregulated hyperemia, leading to destruction of the intervertebral articulations. The progressive and destructive nature of SNA causes substantial deformity, loss of function, and often further neurologic deficits. Patients present with deformity, back pain, audible noises during movement, or new neurologic symptoms. The mainstay of treatment is surgical débridement, reduction, and fusion. The radiologist can help initiate early intervention by using key imaging features to distinguish SNA from imaging mimics and prevent further neurologic deterioration. (©)RSNA, 2016. PMID:27058729

  20. Shape Adaptive, Robust Iris Feature Extraction from Noisy Iris Images

    PubMed Central

    Ghodrati, Hamed; Dehghani, Mohammad Javad; Danyali, Habibolah

    2013-01-01

    In the current iris recognition systems, noise removing step is only used to detect noisy parts of the iris region and features extracted from there will be excluded in matching step. Whereas depending on the filter structure used in feature extraction, the noisy parts may influence relevant features. To the best of our knowledge, the effect of noise factors on feature extraction has not been considered in the previous works. This paper investigates the effect of shape adaptive wavelet transform and shape adaptive Gabor-wavelet for feature extraction on the iris recognition performance. In addition, an effective noise-removing approach is proposed in this paper. The contribution is to detect eyelashes and reflections by calculating appropriate thresholds by a procedure called statistical decision making. The eyelids are segmented by parabolic Hough transform in normalized iris image to decrease computational burden through omitting rotation term. The iris is localized by an accurate and fast algorithm based on coarse-to-fine strategy. The principle of mask code generation is to assign the noisy bits in an iris code in order to exclude them in matching step is presented in details. An experimental result shows that by using the shape adaptive Gabor-wavelet technique there is an improvement on the accuracy of recognition rate. PMID:24696801

  1. Shape adaptive, robust iris feature extraction from noisy iris images.

    PubMed

    Ghodrati, Hamed; Dehghani, Mohammad Javad; Danyali, Habibolah

    2013-10-01

    In the current iris recognition systems, noise removing step is only used to detect noisy parts of the iris region and features extracted from there will be excluded in matching step. Whereas depending on the filter structure used in feature extraction, the noisy parts may influence relevant features. To the best of our knowledge, the effect of noise factors on feature extraction has not been considered in the previous works. This paper investigates the effect of shape adaptive wavelet transform and shape adaptive Gabor-wavelet for feature extraction on the iris recognition performance. In addition, an effective noise-removing approach is proposed in this paper. The contribution is to detect eyelashes and reflections by calculating appropriate thresholds by a procedure called statistical decision making. The eyelids are segmented by parabolic Hough transform in normalized iris image to decrease computational burden through omitting rotation term. The iris is localized by an accurate and fast algorithm based on coarse-to-fine strategy. The principle of mask code generation is to assign the noisy bits in an iris code in order to exclude them in matching step is presented in details. An experimental result shows that by using the shape adaptive Gabor-wavelet technique there is an improvement on the accuracy of recognition rate. PMID:24696801

  2. A feature-enriched completely blind image quality evaluator.

    PubMed

    Lin Zhang; Lei Zhang; Bovik, Alan C

    2015-08-01

    Existing blind image quality assessment (BIQA) methods are mostly opinion-aware. They learn regression models from training images with associated human subjective scores to predict the perceptual quality of test images. Such opinion-aware methods, however, require a large amount of training samples with associated human subjective scores and of a variety of distortion types. The BIQA models learned by opinion-aware methods often have weak generalization capability, hereby limiting their usability in practice. By comparison, opinion-unaware methods do not need human subjective scores for training, and thus have greater potential for good generalization capability. Unfortunately, thus far no opinion-unaware BIQA method has shown consistently better quality prediction accuracy than the opinion-aware methods. Here, we aim to develop an opinion-unaware BIQA method that can compete with, and perhaps outperform, the existing opinion-aware methods. By integrating the features of natural image statistics derived from multiple cues, we learn a multivariate Gaussian model of image patches from a collection of pristine natural images. Using the learned multivariate Gaussian model, a Bhattacharyya-like distance is used to measure the quality of each image patch, and then an overall quality score is obtained by average pooling. The proposed BIQA method does not need any distorted sample images nor subjective quality scores for training, yet extensive experiments demonstrate its superior quality-prediction performance to the state-of-the-art opinion-aware BIQA methods. The MATLAB source code of our algorithm is publicly available at www.comp.polyu.edu.hk/~cslzhang/IQA/ILNIQE/ILNIQE.htm. PMID:25915960

  3. Magnetic Resonance Imaging Features of Adenosis in the Breast

    PubMed Central

    Gity, Masoumeh; Arabkheradmand, Ali; Shakiba, Madjid; Khademi, Yassaman; Bijan, Bijan; Sadaghiani, Mohammad Salehi; Jalali, Amir Hossein

    2015-01-01

    Purpose Adenosis lesions of the breast, including sclerosing adenosis and adenosis tumors, are a group of benign proliferative disorders that may mimic the features of malignancy on imaging. In this study, we aim to describe the features of breast adenosis lesions with suspicious or borderline findings on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Methods In our database, we identified 49 pathologically proven breast adenosis lesions for which the final assessment of the breast MRI report was classified as either category 4 (n=45) or category 5 (n=4), according to the Breast Imaging Reporting and Data System (BI-RADS) published by the American College of Radiology (ACR). The lesions had a final diagnosis of either pure adenosis (n=33, 67.3%) or mixed adenosis associated with other benign pathologies (n=16, 32.7%). Results Of the 49 adenosis lesions detected on DCE-MRI, 32 (65.3%) appeared as enhancing masses, 16 (32.7%) as nonmass enhancements, and one (2.1%) as a tiny enhancing focus. Analysis of the enhancing masses based on the ACR BI-RADS lexicon revealed that among the mass descriptors, the most common features were irregular shape in 12 (37.5%), noncircumscribed margin in 20 (62.5%), heterogeneous internal pattern in 16 (50.0%), rapid initial enhancement in 32 (100.0%), and wash-out delayed en-hancement pattern in 21 (65.6%). Of the 16 nonmass enhancing lesions, the most common descriptors included focal distribution in seven (43.8%), segmental distribution in six (37.5%), clumped internal pattern in nine (56.3%), rapid initial enhancement in 16 (100.0%), and wash-out delayed enhancement pattern in eight (50.0%). Conclusion Adenosis lesions of the breast may appear suspicious on breast MRI. Awareness of these suspi-cious-appearing features would be helpful in obviating unnecessary breast biopsies. PMID:26155296

  4. Development of an Expert System as a Diagnostic Support of Cervical Cancer in Atypical Glandular Cells, Based on Fuzzy Logics and Image Interpretation

    PubMed Central

    Domínguez Hernández, Karem R.; Aguilar Lasserre, Alberto A.; Posada Gómez, Rubén; Palet Guzmán, José A.; González Sánchez, Blanca E.

    2013-01-01

    Cervical cancer is the second largest cause of death among women worldwide. Nowadays, this disease is preventable and curable at low cost and low risk when an accurate diagnosis is done in due time, since it is the neoplasm with the highest prevention potential. This work describes the development of an expert system able to provide a diagnosis to cervical neoplasia (CN) precursor injuries through the integration of fuzzy logics and image interpretation techniques. The key contribution of this research focuses on atypical cases, specifically on atypical glandular cells (AGC). The expert system consists of 3 phases: (1) risk diagnosis which consists of the interpretation of a patient's clinical background and the risks for contracting CN according to specialists; (2) cytology images detection which consists of image interpretation (IM) and the Bethesda system for cytology interpretation, and (3) determination of cancer precursor injuries which consists of in retrieving the information from the prior phases and integrating the expert system by means of a fuzzy logics (FL) model. During the validation stage of the system, 21 already diagnosed cases were tested with a positive correlation in which 100% effectiveness was obtained. The main contribution of this work relies on the reduction of false positives and false negatives by providing a more accurate diagnosis for CN. PMID:23690881

  5. Feature detection on 3D images of dental imprints

    NASA Astrophysics Data System (ADS)

    Mokhtari, Marielle; Laurendeau, Denis

    1994-09-01

    A computer vision approach for the extraction of feature points on 3D images of dental imprints is presented. The position of feature points are needed for the measurement of a set of parameters for automatic diagnosis of malocclusion problems in orthodontics. The system for the acquisition of the 3D profile of the imprint, the procedure for the detection of the interstices between teeth, and the approach for the identification of the type of tooth are described, as well as the algorithm for the reconstruction of the surface of each type of tooth. A new approach for the detection of feature points, called the watershed algorithm, is described in detail. The algorithm is a two-stage procedure which tracks the position of local minima at four different scales and produces a final map of the position of the minima. Experimental results of the application of the watershed algorithm on actual 3D images of dental imprints are presented for molars, premolars and canines. The segmentation approach for the analysis of the shape of incisors is also described in detail.

  6. New features for detecting cervical precancer using hyperspectral diagnostic imaging

    NASA Astrophysics Data System (ADS)

    Okimoto, Gordon S.; Parker, Mary F.; Mooradian, Gregory C.; Saggese, Steven J.; Grisanti, Ames A.; O'Connor, Dennis M.; Miyazawa, Kunio

    2001-05-01

    Principal component analysis (PCA) in the wavelet domain provides powerful new features for the non-invasive detection of cervical intraepithelial neoplasia (CIN) using fluorescence imaging spectroscopy. These features are known as principal wavelet components (PWCs). The multiscale structure of the fluorescence spectrum for each pixel of the hyperspectral data cube is extracted using the continuous wavelet transform. PCA is then used to compress and denoise the wavelet representation for presentation to a feed- forward neural network for tissue classification. Using PWC features as inputs to a 5-class NN resulted in average correct classification rates of 95% over five cervical tissue classes corresponding to low-grade dysplasia, squamous, columnar, metaplasia plus a fifth class for other unspecified tissue types, blood and mucus. A 2-class NN was also trained to discriminate between CIN1 and normal tissue with sensitivity and specificity of 98% and 99%, respectively. All performance assessments were based on test data from a set of patients not seen during NN training. Trained neural classifiers were used to `compress' and transform 3D hyperspectral data cubes into 2D color-coded images that accurately mapped the spatial distribution of both normal and dysplastic tissue over the surface of the entire cervix.

  7. Breast cancer detection in rotational thermography images using texture features

    NASA Astrophysics Data System (ADS)

    Francis, Sheeja V.; Sasikala, M.; Bhavani Bharathi, G.; Jaipurkar, Sandeep D.

    2014-11-01

    Breast cancer is a major cause of mortality in young women in the developing countries. Early diagnosis is the key to improve survival rate in cancer patients. Breast thermography is a diagnostic procedure that non-invasively images the infrared emissions from breast surface to aid in the early detection of breast cancer. Due to limitations in imaging protocol, abnormality detection by conventional breast thermography, is often a challenging task. Rotational thermography is a novel technique developed in order to overcome the limitations of conventional breast thermography. This paper evaluates this technique's potential for automatic detection of breast abnormality, from the perspective of cold challenge. Texture features are extracted in the spatial domain, from rotational thermogram series, prior to and post the application of cold challenge. These features are fed to a support vector machine for automatic classification of normal and malignant breasts, resulting in a classification accuracy of 83.3%. Feature reduction has been performed by principal component analysis. As a novel attempt, the ability of this technique to locate the abnormality has been studied. The results of the study indicate that rotational thermography holds great potential as a screening tool for breast cancer detection.

  8. Automatic archaeological feature extraction from satellite VHR images

    NASA Astrophysics Data System (ADS)

    Jahjah, Munzer; Ulivieri, Carlo

    2010-05-01

    Archaeological applications need a methodological approach on a variable scale able to satisfy the intra-site (excavation) and the inter-site (survey, environmental research). The increased availability of high resolution and micro-scale data has substantially favoured archaeological applications and the consequent use of GIS platforms for reconstruction of archaeological landscapes based on remotely sensed data. Feature extraction of multispectral remotely sensing image is an important task before any further processing. High resolution remote sensing data, especially panchromatic, is an important input for the analysis of various types of image characteristics; it plays an important role in the visual systems for recognition and interpretation of given data. The methods proposed rely on an object-oriented approach based on a theory for the analysis of spatial structures called mathematical morphology. The term "morphology" stems from the fact that it aims at analysing object shapes and forms. It is mathematical in the sense that the analysis is based on the set theory, integral geometry, and lattice algebra. Mathematical morphology has proven to be a powerful image analysis technique; two-dimensional grey tone images are seen as three-dimensional sets by associating each image pixel with an elevation proportional to its intensity level. An object of known shape and size, called the structuring element, is then used to investigate the morphology of the input set. This is achieved by positioning the origin of the structuring element to every possible position of the space and testing, for each position, whether the structuring element either is included or has a nonempty intersection with the studied set. The shape and size of the structuring element must be selected according to the morphology of the searched image structures. Other two feature extraction techniques were used, eCognition and ENVI module SW, in order to compare the results. These techniques were

  9. Buried target detection in FLIR images using Shearlet features

    NASA Astrophysics Data System (ADS)

    Tuomanen, Brian; Stone, Kevin; Madison, Timothy; Popescu, Mihail; Keller, James

    2013-06-01

    In this paper we investigate a new approach for representing objects in FLIR images based on shearlets. Similar to wavelets, shearlets represent an affine system for image representation obtained by scaling and translation of a generating function called mother shearlet. Unlike wavelets, the mother shearlet has an extra parameter called shear that allows the shearlet transform to be anisotropic. Anisotropic property of the shearlet transform could allow for a better representation of objects with irregular shape. We test our representation methodology on Froward looking long wave infrared (LWIR) images obtained from an IR camera installed on a moving vehicle. Objects of interest (spots) are detected in each frame using a prescreener presented in our previous work. Each spot is then represented using its shearlet features and assigned a confidence coming from a support vector machine classifier. We compare shearlets to various traditional features such as local binary patterns (LPB) and histogram of gradients (HOG). The comparison is performed on a large dataset that consists of 16 runs at a US Army test site.

  10. Collaborative Tracking of Image Features Based on Projective Invariance

    NASA Astrophysics Data System (ADS)

    Jiang, Jinwei

    -mode sensors for improving the flexibility and robustness of the system. From the experimental results during three field tests for the LASOIS system, we observed that most of the errors in the image processing algorithm are caused by the incorrect feature tracking. This dissertation addresses the feature tracking problem in image sequences acquired from cameras. Despite many alternatives to feature tracking problem, iterative least squares solution solving the optical flow equation has been the most popular approach used by many in the field. This dissertation attempts to leverage the former efforts to enhance feature tracking methods by introducing a view geometric constraint to the tracking problem, which provides collaboration among features. In contrast to alternative geometry based methods, the proposed approach provides an online solution to optical flow estimation in a collaborative fashion by exploiting Horn and Schunck flow estimation regularized by view geometric constraints. Proposed collaborative tracker estimates the motion of a feature based on the geometry of the scene and how the other features are moving. Alternative to this approach, a new closed form solution to tracking that combines the image appearance with the view geometry is also introduced. We particularly use invariants in the projective coordinates and conjecture that the traditional appearance solution can be significantly improved using view geometry. The geometric constraint is introduced by defining a new optical flow equation which exploits the scene geometry from a set drawn from tracked features. At the end of each tracking loop the quality of the tracked features is judged using both appearance similarity and geometric consistency. Our experiments demonstrate robust tracking performance even when the features are occluded or they undergo appearance changes due to projective deformation of the template. The proposed collaborative tracking method is also tested in the visual navigation

  11. Multimodal Ultrawide-Field Imaging Features in Waardenburg Syndrome.

    PubMed

    Choudhry, Netan; Rao, Rajesh C

    2015-06-01

    A 45-year-old woman was referred for bilateral irregular fundus pigmentation. Dilated fundus examination revealed irregular hypopigmentation posterior to the equator in both eyes, confirmed by fundus autofluorescence. A thickened choroid was seen on enhanced-depth imaging spectral-domain optical coherence tomography (EDI SD-OCT). Systemic evaluation revealed sensorineural deafness, telecanthus, and a white forelock. Further investigation revealed a first-degree relative with Waardenburg syndrome. Waardenburg syndrome is characterized by a group of features including telecanthus, a broad nasal root, synophrys of the eyebrows, piedbaldism, heterochromia irides, and deafness. Choroidal hypopigmentation is a unique feature that can be visualized with ultrawide-field fundus autofluorescence. The choroid may also be thickened and its thickness measured with EDI SD-OCT. PMID:26114849

  12. Random projections based feature-specific structured imaging.

    PubMed

    Baheti, Pawan K; Neifeld, Mark A

    2008-02-01

    We present a feature-specific imaging system based on the use of structured illumination. The measurements are defined as inner products between the illumination patterns and the object reflectance function, measured on a single photodetector. The illumination patterns are defined using random binary patterns and thus do not employ prior knowledge about the object. Object estimates are generated using L(1)-norm minimization and gradient-projection sparse reconstruction algorithms. The experimental reconstructions show the feasibility of the proposed approach by using 42% fewer measurements than the object dimensionality. PMID:18542256

  13. Feature identification for image-guided transcatheter aortic valve implantation

    NASA Astrophysics Data System (ADS)

    Lang, Pencilla; Rajchl, Martin; McLeod, A. Jonathan; Chu, Michael W.; Peters, Terry M.

    2012-02-01

    Transcatheter aortic valve implantation (TAVI) is a less invasive alternative to open-heart surgery, and is critically dependent on imaging for accurate placement of the new valve. Augmented image-guidance for TAVI can be provided by registering together intra-operative transesophageal echo (TEE) ultrasound and a model derived from pre-operative CT. Automatic contour delineation on TEE images of the aortic root is required for real-time registration. This study develops an algorithm to automatically extract contours on simultaneous cross-plane short-axis and long-axis (XPlane) TEE views, and register these features to a 3D pre-operative model. A continuous max-flow approach is used to segment the aortic root, followed by analysis of curvature to select appropriate contours for use in registration. Results demonstrate a mean contour boundary distance error of 1.3 and 2.8mm for the short and long-axis views respectively, and a mean target registration error of 5.9mm. Real-time image guidance has the potential to increase accuracy and reduce complications in TAVI.

  14. Dermatofibroma: Atypical Presentations.

    PubMed

    Bandyopadhyay, Mousumi Roy; Besra, Mrinal; Dutta, Somasree; Sarkar, Somnath

    2016-01-01

    Dermatofibroma is a common benign fibrohistiocytic tumor and its diagnosis is easy when it presents classical clinicopathological features. However, a dermatofibroma may show a wide variety of clinicopathological variants and, therefore, the diagnosis may be difficult. The typical dermatofibroma generally occurs as a single or multiple firm reddish-brown nodules. We report here two atypical presentations of dermatofibroma - Atrophic dermatofibroma and keloidal presentation of dermatofibroma. Clinical dermal atrophy is a common phenomenon in dermatofibromas as demonstrated by the dimpling on lateral pressure. However, this feature is exaggerated in the atrophic variant of dermatofibroma. Atrophic dermatofibroma is defined by dermal atrophy of more than 50% of the lesion apart from the usual features of common dermatofibroma. The keloidal variant of dermatofibroma should not be overlooked as a simple keloid. The findings of keloidal change in dermatofibromas may support that trauma is a possible cause of dermatofibroma. PMID:26955137

  15. Dermatofibroma: Atypical Presentations

    PubMed Central

    Bandyopadhyay, Mousumi Roy; Besra, Mrinal; Dutta, Somasree; Sarkar, Somnath

    2016-01-01

    Dermatofibroma is a common benign fibrohistiocytic tumor and its diagnosis is easy when it presents classical clinicopathological features. However, a dermatofibroma may show a wide variety of clinicopathological variants and, therefore, the diagnosis may be difficult. The typical dermatofibroma generally occurs as a single or multiple firm reddish-brown nodules. We report here two atypical presentations of dermatofibroma - Atrophic dermatofibroma and keloidal presentation of dermatofibroma. Clinical dermal atrophy is a common phenomenon in dermatofibromas as demonstrated by the dimpling on lateral pressure. However, this feature is exaggerated in the atrophic variant of dermatofibroma. Atrophic dermatofibroma is defined by dermal atrophy of more than 50% of the lesion apart from the usual features of common dermatofibroma. The keloidal variant of dermatofibroma should not be overlooked as a simple keloid. The findings of keloidal change in dermatofibromas may support that trauma is a possible cause of dermatofibroma. PMID:26955137

  16. Line drawing extraction from gray level images by feature integration

    NASA Astrophysics Data System (ADS)

    Yoo, Hoi J.; Crevier, Daniel; Lepage, Richard; Myler, Harley R.

    1994-10-01

    We describe procedures that extract line drawings from digitized gray level images, without use of domain knowledge, by modeling preattentive and perceptual organization functions of the human visual system. First, edge points are identified by standard low-level processing, based on the Canny edge operator. Edge points are then linked into single-pixel thick straight- line segments and circular arcs: this operation serves to both filter out isolated and highly irregular segments, and to lump the remaining points into a smaller number of structures for manipulation by later stages of processing. The next stages consist in linking the segments into a set of closed boundaries, which is the system's definition of a line drawing. According to the principles of Gestalt psychology, closure allows us to organize the world by filling in the gaps in a visual stimulation so as to perceive whole objects instead of disjoint parts. To achieve such closure, the system selects particular features or combinations of features by methods akin to those of preattentive processing in humans: features include gaps, pairs of straight or curved parallel lines, L- and T-junctions, pairs of symmetrical lines, and the orientation and length of single lines. These preattentive features are grouped into higher-level structures according to the principles of proximity, similarity, closure, symmetry, and feature conjunction. Achieving closure may require supplying missing segments linking contour concavities. Choices are made between competing structures on the basis of their overall compliance with the principles of closure and symmetry. Results include clean line drawings of curvilinear manufactured objects. The procedures described are part of a system called VITREO (viewpoint-independent 3-D recognition and extraction of objects).

  17. Iterative feature refinement for accurate undersampled MR image reconstruction.

    PubMed

    Wang, Shanshan; Liu, Jianbo; Liu, Qiegen; Ying, Leslie; Liu, Xin; Zheng, Hairong; Liang, Dong

    2016-05-01

    Accelerating MR scan is of great significance for clinical, research and advanced applications, and one main effort to achieve this is the utilization of compressed sensing (CS) theory. Nevertheless, the existing CSMRI approaches still have limitations such as fine structure loss or high computational complexity. This paper proposes a novel iterative feature refinement (IFR) module for accurate MR image reconstruction from undersampled K-space data. Integrating IFR with CSMRI which is equipped with fixed transforms, we develop an IFR-CS method to restore meaningful structures and details that are originally discarded without introducing too much additional complexity. Specifically, the proposed IFR-CS is realized with three iterative steps, namely sparsity-promoting denoising, feature refinement and Tikhonov regularization. Experimental results on both simulated and in vivo MR datasets have shown that the proposed module has a strong capability to capture image details, and that IFR-CS is comparable and even superior to other state-of-the-art reconstruction approaches. PMID:27032527

  18. Iterative feature refinement for accurate undersampled MR image reconstruction

    NASA Astrophysics Data System (ADS)

    Wang, Shanshan; Liu, Jianbo; Liu, Qiegen; Ying, Leslie; Liu, Xin; Zheng, Hairong; Liang, Dong

    2016-05-01

    Accelerating MR scan is of great significance for clinical, research and advanced applications, and one main effort to achieve this is the utilization of compressed sensing (CS) theory. Nevertheless, the existing CSMRI approaches still have limitations such as fine structure loss or high computational complexity. This paper proposes a novel iterative feature refinement (IFR) module for accurate MR image reconstruction from undersampled K-space data. Integrating IFR with CSMRI which is equipped with fixed transforms, we develop an IFR-CS method to restore meaningful structures and details that are originally discarded without introducing too much additional complexity. Specifically, the proposed IFR-CS is realized with three iterative steps, namely sparsity-promoting denoising, feature refinement and Tikhonov regularization. Experimental results on both simulated and in vivo MR datasets have shown that the proposed module has a strong capability to capture image details, and that IFR-CS is comparable and even superior to other state-of-the-art reconstruction approaches.

  19. Imaging Features of Adult Choledochal Cysts: a Pictorial Review

    PubMed Central

    Park, Seong Jin; Yi, Bum Ha; Lee, A Leum; Moon, Jong Ho; Chang, Yun Woo

    2009-01-01

    Choledochal cysts are rare congenital anomalies which are principally diagnosed by disproportional dilatation of the extrahepatic bile ducts. In addition, choledochal cysts are believed to arise from the anomalous union of the common bile duct and pancreatic duct outside the duodenal wall which is also proximal to the sphincter of the Oddi mechanism. The various types of choledochal cysts have been classified on the basis of these anomalous unions (Komi classification) and their anatomical locations (Todani classification). The multidetector computed tomography with reformatted imaging, magnetic resonance cholangiopancreatography, and an endoscopic retrograde cholangiography represent the important techniques providing the anatomical resolution and detail required to properly diagnose and classify choledochal cysts and their associated abnormal features of the biliary tree, as well as their pancreaticobile duct union. This study describes the various imaging features of a choledochal cyst in adults according to the various types of anomalous unions of the pancreaticobile duct according to Komi's classification and anatomic location according to Todani's classification. Lastly, we also review and discuss the associated abnormal findings developed in biliary systems. PMID:19182506

  20. Atypical Cogan's syndrome mimicking encephalitis.

    PubMed

    Lepur, Dragan; Vranjican, Zoran; Himbele, Josip; Barsić, Bruno; Klinar, Igor

    2004-01-01

    Cogan's syndrome is a rare autoimmune multisystem disease. The main clinical features of typical Cogan's syndrome are vestibuloauditory dysfunction and interstitial keratitis. The authors present a case of atypical Cogan's syndrome with headache, fever, deafness, trigeminal neuralgia and electroencephalographic abnormality which mimicked viral encephalitis. PMID:15307593

  1. Motor features in posterior cortical atrophy and their imaging correlates.

    PubMed

    Ryan, Natalie S; Shakespeare, Timothy J; Lehmann, Manja; Keihaninejad, Shiva; Nicholas, Jennifer M; Leung, Kelvin K; Fox, Nick C; Crutch, Sebastian J

    2014-12-01

    Posterior cortical atrophy (PCA) is a neurodegenerative syndrome characterized by impaired higher visual processing skills; however, motor features more commonly associated with corticobasal syndrome may also occur. We investigated the frequency and clinical characteristics of motor features in 44 PCA patients and, with 30 controls, conducted voxel-based morphometry, cortical thickness, and subcortical volumetric analyses of their magnetic resonance imaging. Prominent limb rigidity was used to define a PCA-motor subgroup. A total of 30% (13) had PCA-motor; all demonstrating asymmetrical left upper limb rigidity. Limb apraxia was more frequent and asymmetrical in PCA-motor, as was myoclonus. Tremor and alien limb phenomena only occurred in this subgroup. The subgroups did not differ in neuropsychological test performance or apolipoprotein E4 allele frequency. Greater asymmetry of atrophy occurred in PCA-motor, particularly involving right frontoparietal and peri-rolandic cortices, putamen, and thalamus. The 9 patients (including 4 PCA-motor) with pathology or cerebrospinal fluid all showed evidence of Alzheimer's disease. Our data suggest that PCA patients with motor features have greater atrophy of contralateral sensorimotor areas but are still likely to have underlying Alzheimer's disease. PMID:25086839

  2. Imaging and Clinicopathologic Features of Esophageal Gastrointestinal Stromal Tumors

    PubMed Central

    Winant, Abbey J.; Gollub, Marc J.; Shia, Jinru; Antonescu, Christina; Bains, Manjit S.; Levine, Marc S.

    2016-01-01

    OBJECTIVE The purpose of this article is to describe the imaging and clinicopathologic characteristics of esophageal gastrointestinal stromal tumors (GISTs) and to emphasize the features that differentiate esophageal GISTs from esophageal leiomyomas. MATERIALS AND METHODS A pathology database search identified all surgically resected or biopsied esophageal GISTs, esophageal leiomyomas, and esophageal leiomyosarcomas from 1994 to 2012. Esophageal GISTs were included only if imaging studies (including CT, fluoroscopic, or 18F-FDG PET/CT scans) and clinical data were available. RESULTS Nineteen esophageal mesenchymal tumors were identified, including eight esophageal GISTs (42%), 10 esophageal leiomyomas (53%), and one esophageal leiomyosarcoma (5%). Four patients (50%) with esophageal GIST had symptoms, including dysphagia in three (38%), cough in one (13%), and chest pain in one (13%). One esophageal GIST appeared on barium study as a smooth submucosal mass. All esophageal GISTs appeared on CT as well-marginated predominantly distal lesions, isoattenuating to muscle, that moderately enhanced after IV contrast agent administration. Compared with esophageal leiomyomas, esophageal GISTs tended to be more distal, larger, and more heterogeneous and showed greater IV enhancement on CT. All esophageal GISTs showed marked avidity (mean maximum standardized uptake value, 16) on PET scans. All esophageal GISTs were positive for c-KIT (a cell-surface transmembrane tyrosine kinase also known as CD117) and CD34. On histopathology, six esophageal GISTs (75%) were of the spindle pattern and two (25%) were of a mixed spindle and epithelioid pattern. Five esophageal GISTs had exon 11 mutations (with imatinib sensitivity). Clinical outcome correlated with treatment strategy (resection plus adjuvant therapy or resection alone) rather than risk stratification. CONCLUSION Esophageal GISTs are unusual but clinically important mesenchymal neoplasms. Although esophageal GISTs and

  3. Atypical β-Catenin Activated Child Hepatocellular Tumor

    PubMed Central

    Unlu, Havva Akmaz; Karakus, Esra; Yazal Erdem, Arzu; Yakut, Zeynep Ilerisoy

    2015-01-01

    Hepatocellular adenomas are a benign, focal, hepatic neoplasm that have been divided into four subtypes according to the genetic and pathological features. The β-catenin activated subtype accounts for 10-15% of all hepatocellular adenomas and specific magnetic resonance imaging features have been defined for different hepatocellular adenomas subtypes. The current study aimed to report the magnetic resonance imaging features of a well differentiated hepatocellular carcinoma that developed on the basis of β-catenin activated hepatocellular adenomas in a child. In this case, atypical diffuse steatosis was determined in the lesion. In the literature, diffuse steatosis, which is defined as a feature of the hepatocyte nuclear factor-1α-inactivated hepatocellular adenomas subtype, has not been previously reported in any β-catenin activated hepatocellular adenomas case. Interlacing magnetic resonance imaging findings between subtypes show that there are still many mysteries about this topic and larger studies are warranted. PMID:26157702

  4. Atypical β-Catenin Activated Child Hepatocellular Tumor.

    PubMed

    Turan, Aynur; Unlu, Havva Akmaz; Karakus, Esra; Yazal Erdem, Arzu; Yakut, Zeynep Ilerisoy

    2015-06-01

    Hepatocellular adenomas are a benign, focal, hepatic neoplasm that have been divided into four subtypes according to the genetic and pathological features. The β-catenin activated subtype accounts for 10-15% of all hepatocellular adenomas and specific magnetic resonance imaging features have been defined for different hepatocellular adenomas subtypes. The current study aimed to report the magnetic resonance imaging features of a well differentiated hepatocellular carcinoma that developed on the basis of β-catenin activated hepatocellular adenomas in a child. In this case, atypical diffuse steatosis was determined in the lesion. In the literature, diffuse steatosis, which is defined as a feature of the hepatocyte nuclear factor-1α-inactivated hepatocellular adenomas subtype, has not been previously reported in any β-catenin activated hepatocellular adenomas case. Interlacing magnetic resonance imaging findings between subtypes show that there are still many mysteries about this topic and larger studies are warranted. PMID:26157702

  5. Testing atypical depression definitions.

    PubMed

    Benazzi, Franco

    2005-01-01

    The evidence supporting the DSM-IV definition of atypical depression (AD) is weak. This study aimed to test different definitions of AD. Major depressive disorder (MDD) patients (N = 254) and bipolar-II (BP-II) outpatients (N = 348) were interviewed consecutively, during major depressive episodes, with the Structured Clinical Interview for DSM-IV. DSM-IV criteria for AD were followed. AD validators were female gender, young onset, BP-II, axis I comorbidity, bipolar family history. Frequency of DSM-IV AD was 43.0%. AD, versus non-AD, was significantly associated with all AD validators, apart from comorbidity when controlling for age and sex. Factor analysis of atypical symptoms found factor 1 including oversleeping, overeating and weight gain (leaden paralysis at trend correlation), and factor 2 including interpersonal sensitivity, mood reactivity, and leaden paralysis. Multiple logistic regression of factor 1 versus AD validators found significant associations with several validators (including bipolar family history), whereas factor 2 had no significant associations. Findings may support a new definition of AD based on the state-dependent features oversleeping and overeating (plus perhaps leaden paralysis) versus the current AD definition based on a combination of state and trait features. Pharmacological studies are required to support any new definition of AD, as the current concept of AD is based on different response to TCA antidepressants versus non-AD. PMID:16175877

  6. SU-E-J-237: Image Feature Based DRR and Portal Image Registration

    SciTech Connect

    Wang, X; Chang, J

    2014-06-01

    Purpose: Two-dimensional (2D) matching of the kV X-ray and digitally reconstructed radiography (DRR) images is an important setup technique for image-guided radiotherapy (IGRT). In our clinics, mutual information based methods are used for this purpose on commercial linear accelerators, but with often needs for manual corrections. This work proved the feasibility that feature based image transform can be used to register kV and DRR images. Methods: The scale invariant feature transform (SIFT) method was implemented to detect the matching image details (or key points) between the kV and DRR images. These key points represent high image intensity gradients, and thus the scale invariant features. Due to the poor image contrast from our kV image, direct application of the SIFT method yielded many detection errors. To assist the finding of key points, the center coordinates of the kV and DRR images were read from the DICOM header, and the two groups of key points with similar relative positions to their corresponding centers were paired up. Using these points, a rigid transform (with scaling, horizontal and vertical shifts) was estimated. We also artificially introduced vertical and horizontal shifts to test the accuracy of our registration method on anterior-posterior (AP) and lateral pelvic images. Results: The results provided a satisfactory overlay of the transformed kV onto the DRR image. The introduced vs. detected shifts were fit into a linear regression. In the AP image experiments, linear regression analysis showed a slope of 1.15 and 0.98 with an R2 of 0.89 and 0.99 for the horizontal and vertical shifts, respectively. The results are 1.2 and 1.3 with R2 of 0.72 and 0.82 for the lateral image shifts. Conclusion: This work provided an alternative technique for kV to DRR alignment. Further improvements in the estimation accuracy and image contrast tolerance are underway.

  7. Imaging trace element distributions in single organelles and subcellular features

    NASA Astrophysics Data System (ADS)

    Kashiv, Yoav; Austin, Jotham R.; Lai, Barry; Rose, Volker; Vogt, Stefan; El-Muayed, Malek

    2016-02-01

    The distributions of chemical elements within cells are of prime importance in a wide range of basic and applied biochemical research. An example is the role of the subcellular Zn distribution in Zn homeostasis in insulin producing pancreatic beta cells and the development of type 2 diabetes mellitus. We combined transmission electron microscopy with micro- and nano-synchrotron X-ray fluorescence to image unequivocally for the first time, to the best of our knowledge, the natural elemental distributions, including those of trace elements, in single organelles and other subcellular features. Detected elements include Cl, K, Ca, Co, Ni, Cu, Zn and Cd (which some cells were supplemented with). Cell samples were prepared by a technique that minimally affects the natural elemental concentrations and distributions, and without using fluorescent indicators. It could likely be applied to all cell types and provide new biochemical insights at the single organelle level not available from organelle population level studies.

  8. Imaging trace element distributions in single organelles and subcellular features

    PubMed Central

    Kashiv, Yoav; Austin, Jotham R.; Lai, Barry; Rose, Volker; Vogt, Stefan; El-Muayed, Malek

    2016-01-01

    The distributions of chemical elements within cells are of prime importance in a wide range of basic and applied biochemical research. An example is the role of the subcellular Zn distribution in Zn homeostasis in insulin producing pancreatic beta cells and the development of type 2 diabetes mellitus. We combined transmission electron microscopy with micro- and nano-synchrotron X-ray fluorescence to image unequivocally for the first time, to the best of our knowledge, the natural elemental distributions, including those of trace elements, in single organelles and other subcellular features. Detected elements include Cl, K, Ca, Co, Ni, Cu, Zn and Cd (which some cells were supplemented with). Cell samples were prepared by a technique that minimally affects the natural elemental concentrations and distributions, and without using fluorescent indicators. It could likely be applied to all cell types and provide new biochemical insights at the single organelle level not available from organelle population level studies. PMID:26911251

  9. Malignant transformation in monostotic fibrous dysplasia: clinical features, imaging features, outcomes in 10 patients, and review.

    PubMed

    Qu, Nan; Yao, Weiwu; Cui, Xiaojiang; Zhang, Huizhen

    2015-01-01

    Malignant transformation in fibrous dysplasia (FD) is uncommon. The purpose of this study was to investigate clinical and imaging features, and outcomes of malignant transformation in monostotic FD.Data for 10 pathologically confirmed malignant transformations in monostotic FD from January 2005 to December 2013 were retrospectively reviewed. Patient data were recorded, and radiographs (n = 10), computed tomography (CT) (n = 5), magnetic resonance (MR) (n = 4), and bone scintigrams (n = 10) were evaluated for lesion location, margin, cortical destruction, marrow involvement, periosteal reaction, and soft tissue mass by 2 musculoskeletal radiologists with agreement by consensus. Clinical features, management, and prognosis were also analyzed for each of the 10 cases.There were 8 male and 2 female patients (mean age 46.5 ± 15.9 years). The affected sites were the femur (n = 4), humerus (n = 2), tibia (n = 3), and ilium (n = 1). Five cases had received previous surgery and 5 cases had no history of surgery. No patients had been given prior irradiation treatment. For the 5 cases with surgery, radiographs and CT showed purely osteolytic lesions with poor margination in the curettage area (n = 5), cortical destruction (n = 5), obvious soft tissue mass (n = 1), and mineralization (n = 2). For the 5 cases without surgery, radiographs and CT identified poorly marginated, osteolytic lesions within or near the area with "ground-glass" opacity (n = 4), cortical erosion (n = 4), and mineralization (n = 2). Magnetic resonance imaging (MRI) also identified lesions with heterogeneous signal intensity and pronounced enhancement. Bone scintigraphy revealed eccentric increased uptake of radionuclide in monostotic lesion (n = 10). Pathology reports revealed osteosarcoma (n = 7), fibrosarcoma (n = 2), and malignant fibrous histiocytoma (MFH) (n = 1). At the end of the study, 1 patient died from tumors, 1

  10. Cassini Imaging of Noncircular Features in Saturn's Rings

    NASA Astrophysics Data System (ADS)

    Spitale, J. N.; Porco, C. C.; Baker, E.; Tiscareno, M.; Burns, J. A.

    2005-08-01

    We report on our initial examination of some of the eccentric features in Saturn's rings observed in Cassini imaging sequences. High-resolution movies and 360-degree azimuthal imaging scans, with radial spatial scales as fine as a few km and longitudinal resolutions as fine as a fraction of a degree, reveal the shapes of these features in great detail. The outer edges of the B ring, anchored by the strongest resonance in Saturn's rings -- the Mimas 2:1 inner Lindblad resonance (ILR) -- shows high-frequency radial departures from a simple m=2 shape, as previously found in Voyager data [1] but now seen with greater precision. The outer edge of the A ring, controlled by the Janus/Epimetheus 7:6 ILR, also appears to depart from the simple m=7 sinusoidal shape expected for this model [1]. High- spatial-frequency azimuthal variability has also been seen in other ring edges throughout the rings and in greater detail in the known narrow eccentric ringlets inhabiting the gaps in Saturn's rings, such as the Huygens gap exterior to the B ring and the Maxwell gap in the C ring, and in newly discovered, more tenuous rings seen in these gaps. The shape of the F-ring core is largely consistent with that determined by Bosh et al. [2], though at fine scales it is highly time-variable (see Chavez et al. and Charnoz et al., this conference). [1] Porco et al., 1984; Icarus 60, 17. [2] Bosh et al., 2002; Icarus 157, 57.

  11. Registration of 3-D images using weighted geometrical features

    SciTech Connect

    Maurer, C.R. Jr.; Aboutanos, G.B.; Dawant, B.M.; Maciunas, R.J.; Fitzpatrick, J.M.

    1996-12-01

    In this paper, the authors present a weighted geometrical features (WGF) registration algorithm. Its efficacy is demonstrated by combining points and a surface. The technique is an extension of Besl and McKay`s iterative closest point (ICP) algorithm. The authors use the WGF algorithm to register X-ray computed tomography (CT) and T2-weighted magnetic resonance (MR) volume head images acquired from eleven patients that underwent craniotomies in a neurosurgical clinical trial. Each patient had five external markers attached to transcutaneous posts screwed into the outer table of the skull. The authors define registration error as the distance between positions of corresponding markers that are not used for registration. The CT and MR images are registered using fiducial points (marker positions) only, a surface only, and various weighted combinations of points and a surface. The CT surface is derived from contours corresponding to the inner surface of the skull. The MR surface is derived from contours corresponding to the cerebrospinal fluid (CSF)-dura interface. Registration using points and a surface is found to be significantly more accurate than registration using only points or a surface.

  12. Covert photo classification by fusing image features and visual attributes.

    PubMed

    Lang, Haitao; Ling, Haibin

    2015-10-01

    In this paper, we study a novel problem of classifying covert photos, whose acquisition processes are intentionally concealed from the subjects being photographed. Covert photos are often privacy invasive and, if distributed over Internet, can cause serious consequences. Automatic identification of such photos, therefore, serves as an important initial step toward further privacy protection operations. The problem is, however, very challenging due to the large semantic similarity between covert and noncovert photos, the enormous diversity in the photographing process and environment of cover photos, and the difficulty to collect an effective data set for the study. Attacking these challenges, we make three consecutive contributions. First, we collect a large data set containing 2500 covert photos, each of them is verified rigorously and carefully. Second, we conduct a user study on how humans distinguish covert photos from noncovert ones. The user study not only provides an important evaluation baseline, but also suggests fusing heterogeneous information for an automatic solution. Our third contribution is a covert photo classification algorithm that fuses various image features and visual attributes in the multiple kernel learning framework. We evaluate the proposed approach on the collected data set in comparison with other modern image classifiers. The results show that our approach achieves an average classification rate (1-EER) of 0.8940, which significantly outperforms other competitors as well as human's performance. PMID:25966474

  13. Automated Image Retrieval of Chest CT Images Based on Local Grey Scale Invariant Features.

    PubMed

    Arrais Porto, Marcelo; Cordeiro d'Ornellas, Marcos

    2015-01-01

    Textual-based tools are regularly employed to retrieve medical images for reading and interpretation using current retrieval Picture Archiving and Communication Systems (PACS) but pose some drawbacks. All-purpose content-based image retrieval (CBIR) systems are limited when dealing with medical images and do not fit well into PACS workflow and clinical practice. This paper presents an automated image retrieval approach for chest CT images based local grey scale invariant features from a local database. Performance was measured in terms of precision and recall, average retrieval precision (ARP), and average retrieval rate (ARR). Preliminary results have shown the effectiveness of the proposed approach. The prototype is also a useful tool for radiology research and education, providing valuable information to the medical and broader healthcare community. PMID:26262345

  14. Relationship between atypical depression and social anxiety disorder.

    PubMed

    Koyuncu, Ahmet; Ertekin, Erhan; Ertekin, Banu Aslantaş; Binbay, Zerrin; Yüksel, Cağrı; Deveci, Erdem; Tükel, Raşit

    2015-01-30

    In this study, we aimed to investigate the effects of atypical and non-atypical depression comorbidity on the clinical characteristics and course of social anxiety disorder (SAD). A total of 247 patients with SAD were enrolled: 145 patients with a current depressive episode (unipolar or bipolar) with atypical features, 43 patients with a current depressive episode with non-atypical features and 25 patients without a lifetime history of depressive episodes were compared regarding sociodemographic and clinical features, comorbidity rates, and severity of SAD, depression and functional impairment. Thirty four patients with a past but not current history of major depressive episodes were excluded from the comparisons. 77.1% of current depressive episodes were associated with atypical features. Age at onset of SAD and age at initial major depressive episode were lower in the group with atypical depression than in the group with non-atypical depression. History of suicide attempts and bipolar disorder comorbidity was more common in the atypical depression group as well. Atypical depression group has higher SAD and depression severity and lower functionality than group with non-atypical depression. Our results indicate that the presence of atypical depression is associated with more severe symptoms and more impairment in functioning in patients with SAD. PMID:25454116

  15. Feature Extraction in Sequential Multimedia Images: with Applications in Satellite Images and On-line Videos

    NASA Astrophysics Data System (ADS)

    Liang, Yu-Li

    Multimedia data is increasingly important in scientific discovery and people's daily lives. Content of massive multimedia is often diverse and noisy, and motion between frames is sometimes crucial in analyzing those data. Among all, still images and videos are commonly used formats. Images are compact in size but do not contain motion information. Videos record motion but are sometimes too big to be analyzed. Sequential images, which are a set of continuous images with low frame rate, stand out because they are smaller than videos and still maintain motion information. This thesis investigates features in different types of noisy sequential images, and the proposed solutions that intelligently combined multiple features to successfully retrieve visual information from on-line videos and cloudy satellite images. The first task is detecting supraglacial lakes above ice sheet in sequential satellite images. The dynamics of supraglacial lakes on the Greenland ice sheet deeply affect glacier movement, which is directly related to sea level rise and global environment change. Detecting lakes above ice is suffering from diverse image qualities and unexpected clouds. A new method is proposed to efficiently extract prominent lake candidates with irregular shapes, heterogeneous backgrounds, and in cloudy images. The proposed system fully automatize the procedure that track lakes with high accuracy. We further cooperated with geoscientists to examine the tracked lakes and found new scientific findings. The second one is detecting obscene content in on-line video chat services, such as Chatroulette, that randomly match pairs of users in video chat sessions. A big problem encountered in such systems is the presence of flashers and obscene content. Because of various obscene content and unstable qualities of videos capture by home web-camera, detecting misbehaving users is a highly challenging task. We propose SafeVchat, which is the first solution that achieves satisfactory

  16. Atypical Presentations of Molar Pregnancy: Diagnostic Roles of Imaging, β-Human Chorionic Gonadotropin Measurement, and p57 Immunostaining.

    PubMed

    Mohamed, Sara A; Al-Hendy, Ayman; Ghamande, Sharad; Chaffin, Joanna; Browne, Paul

    2016-03-01

    In modern practice , the diagnosis of molar pregnancy is made at an early gestational age. The opportunity to diagnose gestational trophoblastic disease (GTD) using sonography alone occurs less frequently. The classic appearance of a "snowstorm" in the endometrial cavity and bilateral theca lutein cysts still applies to the diagnosis of second-trimester GTD. The diagnosis of first-trimester GTD requires increased clinical suspicion. If the sonographic appearance of the pregnancy is atypical, GTD should be included in the differential diagnosis. Additional nonimaging criteria such as serial quantitative β-human chorionic gonadotropin levels, pathologic examination, and p57 (cyclin-dependent kinase inhibitor 1C protein) immunostaining can accurately confirm the diagnosis of GTD. PMID:26860483

  17. Combined optimization of image-gathering and image-processing systems for scene feature detection

    NASA Technical Reports Server (NTRS)

    Halyo, Nesim; Arduini, Robert F.; Samms, Richard W.

    1987-01-01

    The relationship between the image gathering and image processing systems for minimum mean squared error estimation of scene characteristics is investigated. A stochastic optimization problem is formulated where the objective is to determine a spatial characteristic of the scene rather than a feature of the already blurred, sampled and noisy image data. An analytical solution for the optimal characteristic image processor is developed. The Wiener filter for the sampled image case is obtained as a special case, where the desired characteristic is scene restoration. Optimal edge detection is investigated using the Laplacian operator x G as the desired characteristic, where G is a two dimensional Gaussian distribution function. It is shown that the optimal edge detector compensates for the blurring introduced by the image gathering optics, and notably, that it is not circularly symmetric. The lack of circular symmetry is largely due to the geometric effects of the sampling lattice used in image acquisition. The optimal image gathering optical transfer function is also investigated and the results of a sensitivity analysis are shown.

  18. W-transform method for feature-oriented multiresolution image retrieval

    SciTech Connect

    Kwong, M.K.; Lin, B.

    1995-07-01

    Image database management is important in the development of multimedia technology. Since an enormous amount of digital images is likely to be generated within the next few decades in order to integrate computers, television, VCR, cables, telephone and various imaging devices. Effective image indexing and retrieval systems are urgently needed so that images can be easily organized, searched, transmitted, and presented. Here, the authors present a local-feature-oriented image indexing and retrieval method based on Kwong, and Tang`s W-transform. Multiresolution histogram comparison is an effective method for content-based image indexing and retrieval. However, most recent approaches perform multiresolution analysis for whole images but do not exploit the local features present in the images. Since W-transform is featured by its ability to handle images of arbitrary size, with no periodicity assumptions, it provides a natural tool for analyzing local image features and building indexing systems based on such features. In this approach, the histograms of the local features of images are used in the indexing, system. The system not only can retrieve images that are similar or identical to the query images but also can retrieve images that contain features specified in the query images, even if the retrieved images as a whole might be very different from the query images. The local-feature-oriented method also provides a speed advantage over the global multiresolution histogram comparison method. The feature-oriented approach is expected to be applicable in managing large-scale image systems such as video databases and medical image databases.

  19. Image sensor innovations for low light levels with active imaging features

    NASA Astrophysics Data System (ADS)

    Powell, Gareth H.; Fereyre, Pierre

    2015-02-01

    Advances in CMOS imaging enable image capture at lower light levels. Color detection is also possible where human vision becomes less sensitive in night conditions. In daytime conditions, there are a number of climatic conditions such as rain, fog, snow or smoke etc. that render traditional `intelligent' outdoor cameras that perform various forms of detection and identification tasks relatively ineffective. It has been proven that an adapted five transistor pixel CMOS sensor can perform range-gated active imaging that extends considerably the usability of intelligent cameras in the most difficult conditions. This paper discusses advanced state of the art image sensors with embedded features, with emphasis on the everimportant size, weight, power and cost benefits and discusses the new applications that are enabled.

  20. Scalable High-Performance Image Registration Framework by Unsupervised Deep Feature Representations Learning.

    PubMed

    Wu, Guorong; Kim, Minjeong; Wang, Qian; Munsell, Brent C; Shen, Dinggang

    2016-07-01

    Feature selection is a critical step in deformable image registration. In particular, selecting the most discriminative features that accurately and concisely describe complex morphological patterns in image patches improves correspondence detection, which in turn improves image registration accuracy. Furthermore, since more and more imaging modalities are being invented to better identify morphological changes in medical imaging data, the development of deformable image registration method that scales well to new image modalities or new image applications with little to no human intervention would have a significant impact on the medical image analysis community. To address these concerns, a learning-based image registration framework is proposed that uses deep learning to discover compact and highly discriminative features upon observed imaging data. Specifically, the proposed feature selection method uses a convolutional stacked autoencoder to identify intrinsic deep feature representations in image patches. Since deep learning is an unsupervised learning method, no ground truth label knowledge is required. This makes the proposed feature selection method more flexible to new imaging modalities since feature representations can be directly learned from the observed imaging data in a very short amount of time. Using the LONI and ADNI imaging datasets, image registration performance was compared to two existing state-of-the-art deformable image registration methods that use handcrafted features. To demonstrate the scalability of the proposed image registration framework, image registration experiments were conducted on 7.0-T brain MR images. In all experiments, the results showed that the new image registration framework consistently demonstrated more accurate registration results when compared to state of the art. PMID:26552069

  1. Scalable High Performance Image Registration Framework by Unsupervised Deep Feature Representations Learning

    PubMed Central

    Wu, Guorong; Kim, Minjeong; Wang, Qian; Munsell, Brent C.

    2015-01-01

    Feature selection is a critical step in deformable image registration. In particular, selecting the most discriminative features that accurately and concisely describe complex morphological patterns in image patches improves correspondence detection, which in turn improves image registration accuracy. Furthermore, since more and more imaging modalities are being invented to better identify morphological changes in medical imaging data,, the development of deformable image registration method that scales well to new image modalities or new image applications with little to no human intervention would have a significant impact on the medical image analysis community. To address these concerns, a learning-based image registration framework is proposed that uses deep learning to discover compact and highly discriminative features upon observed imaging data. Specifically, the proposed feature selection method uses a convolutional stacked auto-encoder to identify intrinsic deep feature representations in image patches. Since deep learning is an unsupervised learning method, no ground truth label knowledge is required. This makes the proposed feature selection method more flexible to new imaging modalities since feature representations can be directly learned from the observed imaging data in a very short amount of time. Using the LONI and ADNI imaging datasets, image registration performance was compared to two existing state-of-the-art deformable image registration methods that use handcrafted features. To demonstrate the scalability of the proposed image registration framework image registration experiments were conducted on 7.0-tesla brain MR images. In all experiments, the results showed the new image registration framework consistently demonstrated more accurate registration results when compared to state-of-the-art. PMID:26552069

  2. Postmortem imaging: MDCT features of postmortem change and decomposition.

    PubMed

    Levy, Angela D; Harcke, Howard Theodore; Mallak, Craig T

    2010-03-01

    Multidetector computed tomography (MDCT) has emerged as an effective imaging technique to augment forensic autopsy. Postmortem change and decomposition are always present at autopsy and on postmortem MDCT because they begin to occur immediately upon death. Consequently, postmortem change and decomposition on postmortem MDCT should be recognized and not mistaken for a pathologic process or injury. Livor mortis increases the attenuation of vasculature and dependent tissues on MDCT. It may also produce a hematocrit effect with fluid levels in the large caliber blood vessels and cardiac chambers from dependent layering erythrocytes. Rigor mortis and algor mortis have no specific MDCT features. In contrast, decomposition through autolysis, putrefaction, and insect and animal predation produce dramatic alterations in the appearance of the body on MDCT. Autolysis alters the attenuation of organs. The most dramatic autolytic changes on MDCT are seen in the brain where cerebral sulci and ventricles are effaced and gray-white matter differentiation is lost almost immediately after death. Putrefaction produces a pattern of gas that begins with intravascular gas and proceeds to gaseous distension of all anatomic spaces, organs, and soft tissues. Knowledge of the spectrum of postmortem change and decomposition is an important component of postmortem MDCT interpretation. PMID:20010292

  3. Imaging trace element distributions in single organelles and subcellular features

    DOE PAGESBeta

    Kashiv, Yoav; Austin, Jotham R.; Lai, Barry; Rose, Volker; Vogt, Stefan; El-Muayed, Malek

    2016-02-25

    The distributions of chemical elements within cells are of prime importance in a wide range of basic and applied biochemical research. An example is the role of the subcellular Zn distribution in Zn homeostasis in insulin producing pancreatic beta cells and the development of type 2 diabetes mellitus. We combined transmission electron microscopy with micro- and nano-synchrotron X-ray fluorescence to image unequivocally for the first time, to the best of our knowledge, the natural elemental distributions, including those of trace elements, in single organelles and other subcellular features. Detected elements include Cl, K, Ca, Co, Ni, Cu, Zn and Cdmore » (which some cells were supplemented with). Cell samples were prepared by a technique that minimally affects the natural elemental concentrations and distributions, and without using fluorescent indicators.We find it could likely be applied to all cell types and provide new biochemical insights at the single organelle level not available from organelle population level studies.« less

  4. A combinatorial Bayesian and Dirichlet model for prostate MR image segmentation using probabilistic image features

    NASA Astrophysics Data System (ADS)

    Li, Ang; Li, Changyang; Wang, Xiuying; Eberl, Stefan; Feng, Dagan; Fulham, Michael

    2016-08-01

    Blurred boundaries and heterogeneous intensities make accurate prostate MR image segmentation problematic. To improve prostate MR image segmentation we suggest an approach that includes: (a) an image patch division method to partition the prostate into homogeneous segments for feature extraction; (b) an image feature formulation and classification method, using the relevance vector machine, to provide probabilistic prior knowledge for graph energy construction; (c) a graph energy formulation scheme with Bayesian priors and Dirichlet graph energy and (d) a non-iterative graph energy minimization scheme, based on matrix differentiation, to perform the probabilistic pixel membership optimization. The segmentation output was obtained by assigning pixels with foreground and background labels based on derived membership probabilities. We evaluated our approach on the PROMISE-12 dataset with 50 prostate MR image volumes. Our approach achieved a mean dice similarity coefficient (DSC) of 0.90  ±  0.02, which surpassed the five best prior-based methods in the PROMISE-12 segmentation challenge.

  5. A combinatorial Bayesian and Dirichlet model for prostate MR image segmentation using probabilistic image features.

    PubMed

    Li, Ang; Li, Changyang; Wang, Xiuying; Eberl, Stefan; Feng, Dagan; Fulham, Michael

    2016-08-21

    Blurred boundaries and heterogeneous intensities make accurate prostate MR image segmentation problematic. To improve prostate MR image segmentation we suggest an approach that includes: (a) an image patch division method to partition the prostate into homogeneous segments for feature extraction; (b) an image feature formulation and classification method, using the relevance vector machine, to provide probabilistic prior knowledge for graph energy construction; (c) a graph energy formulation scheme with Bayesian priors and Dirichlet graph energy and (d) a non-iterative graph energy minimization scheme, based on matrix differentiation, to perform the probabilistic pixel membership optimization. The segmentation output was obtained by assigning pixels with foreground and background labels based on derived membership probabilities. We evaluated our approach on the PROMISE-12 dataset with 50 prostate MR image volumes. Our approach achieved a mean dice similarity coefficient (DSC) of 0.90  ±  0.02, which surpassed the five best prior-based methods in the PROMISE-12 segmentation challenge. PMID:27461085

  6. An Open Source Agenda for Research Linking Text and Image Content Features.

    ERIC Educational Resources Information Center

    Goodrum, Abby A.; Rorvig, Mark E.; Jeong, Ki-Tai; Suresh, Chitturi

    2001-01-01

    Proposes methods to utilize image primitives to support term assignment for image classification. Proposes to release code for image analysis in a common tool set for other researchers to use. Of particular focus is the expansion of work by researchers in image indexing to include image content-based feature extraction capabilities in their work.…

  7. Image Labeling for LIDAR Intensity Image Using K-Nn of Feature Obtained by Convolutional Neural Network

    NASA Astrophysics Data System (ADS)

    Umemura, Masaki; Hotta, Kazuhiro; Nonaka, Hideki; Oda, Kazuo

    2016-06-01

    We propose an image labeling method for LIDAR intensity image obtained by Mobile Mapping System (MMS) using K-Nearest Neighbor (KNN) of feature obtained by Convolutional Neural Network (CNN). Image labeling assigns labels (e.g., road, cross-walk and road shoulder) to semantic regions in an image. Since CNN is effective for various image recognition tasks, we try to use the feature of CNN (Caffenet) pre-trained by ImageNet. We use 4,096-dimensional feature at fc7 layer in the Caffenet as the descriptor of a region because the feature at fc7 layer has effective information for object classification. We extract the feature by the Caffenet from regions cropped from images. Since the similarity between features reflects the similarity of contents of regions, we can select top K similar regions cropped from training samples with a test region. Since regions in training images have manually-annotated ground truth labels, we vote the labels attached to top K similar regions to the test region. The class label with the maximum vote is assigned to each pixel in the test image. In experiments, we use 36 LIDAR intensity images with ground truth labels. We divide 36 images into training (28 images) and test sets (8 images). We use class average accuracy and pixel-wise accuracy as evaluation measures. Our method was able to assign the same label as human beings in 97.8% of the pixels in test LIDAR intensity images.

  8. Semantic interpretation of robust imaging features for Fuhrman grading of renal carcinoma

    PubMed Central

    Champion, Andrew; Lu, Guolan; Walker, Marcus; Kothari, Sonal; Osunkoya, Adeboye O.; Wang, May D.

    2016-01-01

    Pattern recognition in tissue biopsy images can assist in clinical diagnosis and identify relevant image characteristics linked with various biological characteristics. Although previous work suggests several informative imaging features for pattern recognition, there exists a semantic gap between characteristics of these features and pathologists’ interpretation of histopathological images. To address this challenge, we develop a clinical decision support system for automated Fuhrman grading of renal carcinoma biopsy images. We extract 1316 color, shape, texture and topology features and develop one vs. all models for four Fuhrman grades. Our models are highly accurate with 90.4% accuracy in a four-class prediction. Predictivity analysis suggests good generalization of the model development methodology through robustness to dataset sampling in cross-validation. We provide a semantic interpretation for the imaging features used in these models by linking features to pathologists’ grading criteria. Our study identifies novel imaging features that are semantically linked to Fuhrman grading criteria. PMID:25571472

  9. Important clinical features of atypical antipsychotics in acute bipolar depression that inform routine clinical care: a review of pivotal studies with number needed to treat.

    PubMed

    Gao, Keming; Yuan, Chengmei; Wu, Renrong; Chen, Jun; Wang, Zuowei; Fang, Yiru; Calabrese, Joseph R

    2015-10-01

    English-language literature cited in MEDLINE from January, 1980 to October 30, 2014 was searched by using terms of antipsychotic, generic and brand names of atypical antipsychotics, "bipolar depression/bipolar disorder", "placebo", and "trial". The parameters of response (≥50% improvement on MADRS, Montgomery-Asberg Depression Rating Scale total score), remission (either ≤12 or 8 on MADRS total score at endpoint), discontinuation due to adverse events (DAEs), somnolence, ≥7% weight gain, overall extrapyramidal side-effects (EPSs), and akathisia, were extracted from originally published primary outcome papers. The number needed to treat to benefit (NNT) for response and remission or harm (NNH) for DAEs or other side effects relative to placebo were estimated and presented with the estimate and 95% confidence interval. Olanzapine monotherapy, olanzapine-fluoxetine combination (OFC), quetiapine-IR monotherapy, quetiapine-XR monotherapy, lurasidone monotherapy, and lurasidone adjunctive therapy were superior to placebo with NNTs for responses of 11-12, 4, 7-8, 4, 4-5, and 7, and NNTs for remission of 11-12, 4, 5-11, 7, 6-7, and 6, respectively. There was no significant difference between OFC and lamotrigine, and between aripiprazole or ziprasidone and placebo in response and remission. Olanzapine monotherapy, quetiapine-IR, quetiapine-XR, aripiprazole, and ziprasidone 120-160 mg/day had significantly increased risk for DAEs with NNHs of 24, 8-14, 9, 12, and 10, respectively. For somnolence, quetiapine-XR had the smallest NNH of 4. For ≥7% weight gain, olanzapine monotherapy and OFC had the smallest NNHs with both of 5. For akathisia, aripiprazole had the smallest NNH of 5. These findings suggest that among the FDA-approved agents including OFC, quetiapine-IR and -XR, lurasidone monotherapy and adjunctive therapy to a mood stabilizer, the differences in the NNTs for response and remission are small, but the differences in NNHs for DAEs and common side

  10. Diabetic mastopathy: imaging features and the role of image-guided biopsy in its diagnosis

    PubMed Central

    2016-01-01

    Purpose: The goal of this study was to evaluate the imaging features of diabetic mastopathy (DMP) and the role of image-guided biopsy in its diagnosis. Methods: Two experienced radiologists retrospectively reviewed the mammographic and sonographic images of 19 pathologically confirmed DMP patients. The techniques and results of the biopsies performed in each patient were also reviewed. Results: Mammograms showed negative findings in 78% of the patients. On ultrasonography (US), 13 lesions were seen as masses and six as non-mass lesions. The US features of the mass lesions were as follows: irregular shape (69%), oval shape (31%), indistinct margin (69%), angular margin (15%), microlobulated margin (8%), well-defined margin (8%), heterogeneous echogenicity (62%), hypoechoic echogenicity (38%), posterior shadowing (92%), parallel orientation (100%), the absence of calcifications (100%), and the absence of vascularity (100%). Based on the US findings, 17 lesions (89%) were classified as Breast Imaging Reporting and Data System category 4 and two (11%) as category 3. US-guided core biopsy was performed in 18 patients, and 10 (56%) were diagnosed with DMP on that basis. An additional vacuum-assisted biopsy was performed in seven patients and all were diagnosed with DMP. Conclusion: The US features of DMP were generally suspicious for malignancy, whereas the mammographic findings were often negative or showed only focal asymmetry. Core biopsy is an adequate method for initial pathological diagnosis. However, since it yields non-diagnostic results in a considerable number of cases, the evaluation of correlations between imaging and pathology plays an important role in the diagnostic process. PMID:26810194