PROCEEDINGS VOLUME 9785
SPIE MEDICAL IMAGING | FEB 27 - MAR 3 2016
Medical Imaging 2016: Computer-Aided Diagnosis
Proceedings Volume 9785 is from: Logo
SPIE MEDICAL IMAGING
Feb 27 - Mar 3 2016
San Diego, California, United States
Front Matter: Volume 9785
Proc. SPIE 9785, Front Matter: Volume 9785, 978501 (30 August 2016); doi: 10.1117/12.2240961
Vessels and Heart
Proc. SPIE 9785, Inner and outer coronary vessel wall segmentation from CCTA using an active contour model with machine learning-based 3D voxel context-aware image force, 978502 (24 March 2016); doi: 10.1117/12.2216200
Proc. SPIE 9785, Automated identification of best-quality coronary artery segments from multiple-phase coronary CT angiography (cCTA) for vessel analysis, 978503 (24 March 2016); doi: 10.1117/12.2217261
Proc. SPIE 9785, 3D assessment of the carotid artery vessel wall volume: an imaging biomarker for diagnosis of the atherosclerotic disease, 978504 (24 March 2016); doi: 10.1117/12.2216890
Proc. SPIE 9785, A system for automatic aorta sections measurements on chest CT, 978505 (24 March 2016); doi: 10.1117/12.2217566
Proc. SPIE 9785, Quantitative MRI myocarditis analysis by a PCA-based object recognition algorithm, 978506 (24 March 2016); doi: 10.1117/12.2216050
Musculoskeletal and Miscellaneous
Proc. SPIE 9785, Differentiation of fat, muscle, and edema in thigh MRIs using random forest classification, 978507 (24 March 2016); doi: 10.1117/12.2217606
Proc. SPIE 9785, Assessing vertebral fracture risk on volumetric quantitative computed tomography by geometric characterization of trabecular bone structure, 978508 (24 March 2016); doi: 10.1117/12.2216898
Proc. SPIE 9785, Classification of voting patterns to improve the generalized Hough transform for epiphyses localization, 978509 (24 March 2016); doi: 10.1117/12.2216173
Proc. SPIE 9785, Medical sieve: a cognitive assistant for radiologists and cardiologists, 97850A (24 March 2016); doi: 10.1117/12.2217382
Proc. SPIE 9785, Acne image analysis: lesion localization and classification, 97850B (24 March 2016); doi: 10.1117/12.2216444
Proc. SPIE 9785, Classification of melanoma lesions using sparse coded features and random forests, 97850C (24 March 2016); doi: 10.1117/12.2216973
Lung and Chest I
Proc. SPIE 9785, Localized Fisher vector representation for pathology detection in chest radiographs, 97850D (24 March 2016); doi: 10.1117/12.2217536
Proc. SPIE 9785, Intensity targeted radial structure tensor analysis and its application for automated mediastinal lymph node detection from CT volumes, 97850E (24 March 2016); doi: 10.1117/12.2216663
Proc. SPIE 9785, Automatic aortic root segmentation in CTA whole-body dataset, 97850F (24 March 2016); doi: 10.1117/12.2216734
Proc. SPIE 9785, Effects of CT dose and nodule characteristics on lung-nodule detectability in a cohort of 90 national lung screening trial patients, 97850G (24 March 2016); doi: 10.1117/12.2217405
Proc. SPIE 9785, An automated lung nodule detection system for CT images using synthetic minority oversampling, 97850H (24 March 2016); doi: 10.1117/12.2216357
Breast
Proc. SPIE 9785, Quantification of mammographic masking risk with volumetric breast density maps: how to select women for supplemental screening, 97850I (24 March 2016); doi: 10.1117/12.2216810
Proc. SPIE 9785, Seamless lesion insertion in digital mammography: methodology and reader study, 97850J (24 March 2016); doi: 10.1117/12.2217056
Proc. SPIE 9785, Workflow improvements for digital breast tomosynthesis: computerized generation of enhanced synthetic images, 97850K (24 March 2016); doi: 10.1117/12.2217182
Proc. SPIE 9785, A fully automated system for quantification of background parenchymal enhancement in breast DCE-MRI, 97850L (24 March 2016); doi: 10.1117/12.2211640
Proc. SPIE 9785, Parenchymal texture measures weighted by breast anatomy: preliminary optimization in a case-control study, 97850M (24 March 2016); doi: 10.1117/12.2217697
Proc. SPIE 9785, Automated linking of suspicious findings between automated 3D breast ultrasound volumes, 97850N (24 March 2016); doi: 10.1117/12.2214945
Keynote and Deep Learning I
Proc. SPIE 9785, Deep convolutional networks for automated detection of posterior-element fractures on spine CT, 97850P (24 March 2016); doi: 10.1117/12.2217146
Proc. SPIE 9785, Increasing CAD system efficacy for lung texture analysis using a convolutional network, 97850Q (24 March 2016); doi: 10.1117/12.2217752
Radiomics I
Proc. SPIE 9785, Increasing cancer detection yield of breast MRI using a new CAD scheme of mammograms, 97850R (24 March 2016); doi: 10.1117/12.2208246
Proc. SPIE 9785, Identification, segmentation, and characterization of microcalcifications on mammography, 97850S (24 March 2016); doi: 10.1117/12.2216274
Proc. SPIE 9785, Predicting Ki67% expression from DCE-MR images of breast tumors using textural kinetic features in tumor habitats, 97850T (24 March 2016); doi: 10.1117/12.2216075
Proc. SPIE 9785, Applying quantitative adiposity feature analysis models to predict benefit of bevacizumab-based chemotherapy in ovarian cancer patients, 97850U (24 March 2016); doi: 10.1117/12.2214230
Proc. SPIE 9785, Radiogenomics of glioblastoma: a pilot multi-institutional study to investigate a relationship between tumor shape features and tumor molecular subtype, 97850V (24 March 2016); doi: 10.1117/12.2217084
Proc. SPIE 9785, Prognosis classification in glioblastoma multiforme using multimodal MRI derived heterogeneity textural features: impact of pre-processing choices, 97850W (24 March 2016); doi: 10.1117/12.2217151
Deep Learning II
Proc. SPIE 9785, Detection of soft tissue densities from digital breast tomosynthesis: comparison of conventional and deep learning approaches, 97850X (24 March 2016); doi: 10.1117/12.2217045
Proc. SPIE 9785, Deep-learning convolution neural network for computer-aided detection of microcalcifications in digital breast tomosynthesis, 97850Y (24 March 2016); doi: 10.1117/12.2217092
Proc. SPIE 9785, Computer aided lung cancer diagnosis with deep learning algorithms, 97850Z (24 March 2016); doi: 10.1117/12.2216307
Proc. SPIE 9785, Visualizing and enhancing a deep learning framework using patients age and gender for chest x-ray image retrieval, 978510 (7 July 2016); doi: 10.1117/12.2217587
Proc. SPIE 9785, Deep convolutional neural networks for automatic coronary calcium scoring in a screening study with low-dose chest CT, 978511 (24 March 2016); doi: 10.1117/12.2216978
Proc. SPIE 9785, Comparison of bladder segmentation using deep-learning convolutional neural network with and without level sets, 978512 (24 March 2016); doi: 10.1117/12.2216852
Lung and Chest II
Proc. SPIE 9785, Pulmonary nodule detection using a cascaded SVM classifier, 978513 (24 March 2016); doi: 10.1117/12.2216747
Proc. SPIE 9785, Spatial context learning approach to automatic segmentation of pleural effusion in chest computed tomography images, 978514 (24 March 2016); doi: 10.1117/12.2216958
Proc. SPIE 9785, Lymph node detection in IASLC-defined zones on PET/CT images, 978515 (24 March 2016); doi: 10.1117/12.2217767
Proc. SPIE 9785, Intrapulmonary vascular remodeling: MSCT-based evaluation in COPD and alpha-1 antitrypsin deficient subjects, 978516 (24 March 2016); doi: 10.1117/12.2216522
Proc. SPIE 9785, Automatic heart localization and radiographic index computation in chest x-rays, 978517 (24 March 2016); doi: 10.1117/12.2217209
Head and Neck
Proc. SPIE 9785, Comprehensive eye evaluation algorithm, 978518 (24 March 2016); doi: 10.1117/12.2217130
Proc. SPIE 9785, Vessel discoloration detection in malarial retinopathy, 978519 (24 March 2016); doi: 10.1117/12.2216917
Proc. SPIE 9785, Computer-aided detection of human cone photoreceptor inner segments using multi-scale circular voting, 97851A (24 March 2016); doi: 10.1117/12.2216929
Proc. SPIE 9785, Sweet-spot training for early esophageal cancer detection, 97851B (24 March 2016); doi: 10.1117/12.2208114
Proc. SPIE 9785, A single-layer network unsupervised feature learning method for white matter hyperintensity segmentation, 97851C (24 March 2016); doi: 10.1117/12.2216409
Proc. SPIE 9785, Early esophageal cancer detection using RF classifiers, 97851D (24 March 2016); doi: 10.1117/12.2208583
Radiomics II
Proc. SPIE 9785, Applying a radiomics approach to predict prognosis of lung cancer patients, 97851E (24 March 2016); doi: 10.1117/12.2214672
Proc. SPIE 9785, Radiomics versus physician assessment for the early prediction of local cancer recurrence after stereotactic radiotherapy for lung cancer, 97851F (24 March 2016); doi: 10.1117/12.2217236
Proc. SPIE 9785, Automatic staging of bladder cancer on CT urography, 97851G (24 March 2016); doi: 10.1117/12.2217004
Proc. SPIE 9785, Signal intensity analysis of ecological defined habitat in soft tissue sarcomas to predict metastasis development, 97851H (24 March 2016); doi: 10.1117/12.2216961
Proc. SPIE 9785, Classification of progression free survival with nasopharyngeal carcinoma tumors, 97851I (24 March 2016); doi: 10.1117/12.2216976
Colon and Prostate
Proc. SPIE 9785, Decision forests for learning prostate cancer probability maps from multiparametric MRI, 97851J (24 March 2016); doi: 10.1117/12.2216904
Proc. SPIE 9785, Fusion of multi-parametric MRI and temporal ultrasound for characterization of prostate cancer: in vivo feasibility study, 97851K (24 March 2016); doi: 10.1117/12.2217205