Deep learning of 3D computed tomography (CT) images for organ segmentation using 2D multi-channel SegNet model
Combining deep learning methods and human knowledge to identify abnormalities in computed tomography (CT) reports
Improving classification with forced labeling of other related classes: application to prediction of upstaged ductal carcinoma in situ using mammographic features
Breast tumor segmentation in DCE-MRI using fully convolutional networks with an application in radiogenomics
Association of high proliferation marker Ki-67 expression with DCEMR imaging features of breast: a large scale evaluation
Deep learning-based features of breast MRI for prediction of occult invasive disease following a diagnosis of ductal carcinoma in situ: preliminary data
Breast mass detection in mammography and tomosynthesis via fully convolutional network-based heatmap regression
Learning better deep features for the prediction of occult invasive disease in ductal carcinoma in situ through transfer learning
Radiogenomic analysis of lower grade glioma: a pilot multi-institutional study shows an association between quantitative image features and tumor genomics
Can BI-RADS features on mammography be used as a surrogate for expensive genomic testing in breast cancer patients?
Statistical aspects of radiogenomics: can radiogenomics models be used to aid prediction of outcomes in cancer patients?
Prediction of occult invasive disease in ductal carcinoma in situ using computer-extracted mammographic features
Deep learning for segmentation of brain tumors: can we train with images from different institutions?
Can upstaging of ductal carcinoma in situ be predicted at biopsy by histologic and mammographic features?
Radiogenomics of glioblastoma: a pilot multi-institutional study to investigate a relationship between tumor shape features and tumor molecular subtype
Identification of error making patterns in lesion detection on digital breast tomosynthesis using computer-extracted image features
Predicting outcomes in glioblastoma patients using computerized analysis of tumor shape: preliminary data
Incorporating breast tomosynthesis into radiology residency: Does trainee experience in breast imaging translate into improved performance with this new modality?
Modeling resident error-making patterns in detection of mammographic masses using computer-extracted image features: preliminary experiments
Modeling error in assessment of mammographic image features for improved computer-aided mammography training: initial experience
Perception-driven IT-CADe analysis for the detection of masses in screening mammography: initial investigation
A comparative study of database reduction methods for case-based computer-aided detection systems: preliminary results
Relational representation for improved decisions with an information-theoretic CADe system: initial experience
Database decomposition of a knowledge-based CAD system in mammography: an ensemble approach to improve detection
Toward perceptually driven image retrieval in mammography: a pilot observer study to assess visual similarity of masses