51 citations · 57 across the 9 of their papers we have counts for
7 papers · 1 filter
Mask Enhanced Deeply Supervised Prostate Cancer Detection on B-mode Micro-Ultrasound
Lichun Zhang, Steve Ran Zhou, Moon Hyung Choi +14
Prostate cancer is a leading cause of cancer-related deaths among men. The recent development of high frequency, micro-ultrasound imaging offers improved resolution compared to con…
Correlated Feature Aggregation by Region Helps Distinguish Aggressive from Indolent Clear Cell Renal Cell Carcinoma Subtypes on CT
Karin Stacke, Indrani Bhattacharya, Justin R. Tse +3
Renal cell carcinoma (RCC) is a common cancer that varies in clinical behavior. Indolent RCC is often low-grade without necrosis and can be monitored without treatment. Aggressive…
Image quality assessment for machine learning tasks using meta-reinforcement learning
Shaheer U. Saeed, Yunguan Fu, Vasilis Stavrinides +8
In this paper, we consider image quality assessment (IQA) as a measure of how images are amenable with respect to a given downstream task, or task amenability. When the task is per…
Weakly Supervised Registration of Prostate MRI and Histopathology Images
Wei Shao, Indrani Bhattacharya, Simon J. C. Soerensen +7
The interpretation of prostate MRI suffers from low agreement across radiologists due to the subtle differences between cancer and normal tissue. Image registration addresses this…
ProsRegNet: A Deep Learning Framework for Registration of MRI and Histopathology Images of the Prostate
Wei Shao, Linda Banh, Christian A. Kunder +10
Magnetic resonance imaging (MRI) is an increasingly important tool for the diagnosis and treatment of prostate cancer. However, interpretation of MRI suffers from high inter-observ…
CorrSigNet: Learning CORRelated Prostate Cancer SIGnatures from Radiology and Pathology Images for Improved Computer Aided Diagnosis
Indrani Bhattacharya, Arun Seetharaman, Wei Shao +10
Magnetic Resonance Imaging (MRI) is widely used for screening and staging prostate cancer. However, many prostate cancers have subtle features which are not easily identifiable on…