about
A new automated method for the segmentation and characterization of breast masses on ultrasound images.Digital mammography: observer performance study of the effects of pixel size on the characterization of malignant and benign microcalcifications.Inter-Method Performance Study of Tumor Volumetry Assessment on Computed Tomography Test-Retest Data.Computer-aided detection of pulmonary embolism in computed tomographic pulmonary angiography (CTPA): performance evaluation with independent data setsAdvances in computer-aided diagnosis for breast cancer.Computer-aided detection system for breast masses on digital tomosynthesis mammograms: preliminary experience.Computer-aided diagnosis of lung cancer and pulmonary embolism in computed tomography-a review.Malignant and benign breast masses on 3D US volumetric images: effect of computer-aided diagnosis on radiologist accuracyComputer-aided detection of lung nodules: false positive reduction using a 3D gradient field method and 3D ellipsoid fitting.Dynamic multiple thresholding breast boundary detection algorithm for mammograms.Computer-aided detection of masses in digital tomosynthesis mammography: comparison of three approaches.Effect of CAD on radiologists' detection of lung nodules on thoracic CT scans: analysis of an observer performance study by nodule size.Effect of finite sample size on feature selection and classification: a simulation studyComputer-aided diagnosis of pulmonary nodules on CT scans: improvement of classification performance with nodule surface features.Computerized image analysis: texture-field orientation method for pectoral muscle identification on MLO-view mammograms.Similarity evaluation in a content-based image retrieval (CBIR) CADx system for characterization of breast masses on ultrasound images.Evaluation of computer-aided detection and diagnosis systems.Computerized nipple identification for multiple image analysis in computer-aided diagnosisA diffusion-based truncated projection artifact reduction method for iterative digital breast tomosynthesis reconstructionSelective-diffusion regularization for enhancement of microcalcifications in digital breast tomosynthesis reconstruction.Joint two-view information for computerized detection of microcalcifications on mammograms.Digital breast tomosynthesis: studies of the effects of acquisition geometry on contrast-to-noise ratio and observer preference of low-contrast objects in breast phantom images.Multiscale bilateral filtering for improving image quality in digital breast tomosynthesis.Coronary CT angiography (cCTA): automated registration of coronary arterial trees from multiple phases.Digital breast tomosynthesis: computer-aided detection of clustered microcalcifications on planar projection imagesDigital breast tomosynthesis: observer performance of clustered microcalcification detection on breast phantom images acquired with an experimental system using variable scan angles, angular increments, and number of projection views.Association of computerized mammographic parenchymal pattern measure with breast cancer risk: a pilot case-control study.Image quality of microcalcifications in digital breast tomosynthesis: effects of projection-view distributions.Digital breast tomosynthesis is comparable to mammographic spot views for mass characterization.Computer-aided detection of clustered microcalcifications in digital breast tomosynthesis: a 3D approach.Detection of urinary bladder mass in CT urography with SPAN.LUNGx Challenge for computerized lung nodule classification: reflections and lessons learnedComputer-aided detection systems for breast masses: comparison of performances on full-field digital mammograms and digitized screen-film mammogramsA similarity study of content-based image retrieval system for breast cancer using decision treeBreast masses: computer-aided diagnosis with serial mammograms.Computer-aided detection system for clustered microcalcifications in digital breast tomosynthesis using joint information from volumetric and planar projection imagesAuto-initialized cascaded level set (AI-CALS) segmentation of bladder lesions on multidetector row CT urographyTreatment Response Assessment for Bladder Cancer on CT Based on Computerized Volume Analysis, World Health Organization Criteria, and RECIST.Urinary bladder segmentation in CT urography using deep-learning convolutional neural network and level sets.Head and neck cancers on CT: preliminary study of treatment response assessment based on computerized volume analysis.
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Lubomir Hadjiiski
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Lubomir Hadjiiski
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Lubomir Hadjiiski
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Lubomir Hadjiiski
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Lubomir Hadjiiski
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Lubomir Hadjiiski
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P214
P244
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