3 citations · 4 across the 3 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…
eess.IV2019★ 1 cited
Improvement of Multiparametric MR Image Segmentation by Augmenting the Data with Generative Adversarial Networks for Glioma Patients
Eric Carver, Zhenzhen Dai, Evan Liang +2
Every year thousands of patients are diagnosed with a glioma, a type of malignant brain tumor. Physicians use MR images as a key tool in the diagnosis and treatment of these patien…
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…