3 citations · 3 across the 2 of their papers we have counts for
3 papers
eess.IV2020
Accurate Prostate Cancer Detection and Segmentation on Biparametric MRI using Non-local Mask R-CNN with Histopathological Ground Truth
Zhenzhen Dai, Ivan Jambor, Pekka Taimen +8
Purpose: We aimed to develop deep machine learning (DL) models to improve the detection and segmentation of intraprostatic lesions (IL) on bp-MRI by using whole amount prostatectom…
cs.CV2019★ 3 cited
Segmentation of the Prostatic Gland and the Intraprostatic Lesions on Multiparametic MRI Using Mask-RCNN
Zhenzhen Dai, Eric Carver, Chang Liu +6
Prostate cancer (PCa) is the most common cancer in men in the United States. Multiparametic magnetic resonance imaging (mp-MRI) has been explored by many researchers to targeted pr…
cs.CV2019
A Deep Dive into Understanding Tumor Foci Classification using Multiparametric MRI Based on Convolutional Neural Network
Weiwei Zong, Joon Lee, Chang Liu +9
Deep learning models have had a great success in disease classifications using large data pools of skin cancer images or lung X-rays. However, data scarcity has been the roadblock…