3 citations · 4 across the 3 of their papers we have counts for
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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…