Evolution-based Fine-tuning of CNNs for Prostate Cancer Detection

no code implementations • 4 Nov 2019 • Khashayar Namdar, Isha Gujrathi, Masoom A. Haider, Farzad Khalvati

Convolutional Neural Networks (CNNs) have been used for automated detection of prostate cancer where Area Under Receiver Operating Characteristic (ROC) curve (AUC) is usually used as the performance metric.

A Transfer Learning Approach for Automated Segmentation of Prostate Whole Gland and Transition Zone in Diffusion Weighted MRI

no code implementations • 20 Sep 2019 • Saman Motamed, Isha Gujrathi, Dominik Deniffel, Anton Oentoro, Masoom A. Haider, Farzad Khalvati

Using a fine-tuning data of 115 patients from the target domain, dice score coefficient of 0. 85 and 0. 84 are achieved for segmentation of whole gland and transition zone, respectively, in the target domain.

Segmentation Transfer Learning

Prostate Cancer Detection using Deep Convolutional Neural Networks

no code implementations • 30 May 2019 • Sunghwan Yoo, Isha Gujrathi, Masoom A. Haider, Farzad Khalvati

As an integrated part of computer-aided detection (CAD) tools, diffusion-weighted magnetic resonance imaging (DWI) has been intensively studied for accurate detection of prostate cancer.

object-detection Object Detection