no code implementations • 3 Mar 2023 • Scott Schoen Jr, Viksit Kumar, Yuyang Gu, Sunethra Dayavansha, Rimon Tadross, Mike Washburn, Kai Thomenius, Anthony E. Samir
Diagnostic ultrasound is a versatile and practical tool in the abdomen, and is particularly vital toward the detection and mitigation of early-stage non-alcoholic fatty liver disease (NAFLD).
no code implementations • 23 Jan 2021 • Shuhang Wang, Vivek Kumar Singh, Alex Benjamin, Mercy Asiedu, Elham Yousef Kalafi, Eugene Cheah, Viksit Kumar, Anthony Samir
The salient features of our algorithm include: 1)no need for original training data or generative networks, 2) knowledge transfer between different architectures, 3) ease of implementation for downstream tasks by using the downstream task dataset as the transferal dataset, 4) knowledge transfer of an ensemble of models, trained independently, into one student model.
no code implementations • 1 Jan 2021 • Shuhang Wang, Eugene Cheah, Elham Yousef Kalafi, Mercy Asiedu, Alex Benjamin, Vivek Kumar Singh, Ge Zhang, Viksit Kumar, Anthony Edward Samir
Transfer learning often employs all or part of the weights of a pre-trained net-work to the problem at hand; this limits the flexibility of new neural architectures.
no code implementations • 7 Apr 2020 • Shuhang Wang, Szu-Yeu Hu, Eugene Cheah, XiaoHong Wang, JingChao Wang, Lei Chen, Masoud Baikpour, Arinc Ozturk, Qian Li, Shinn-Huey Chou, Constance D. Lehman, Viksit Kumar, Anthony Samir
This paper proposes a novel U-Net variant using stacked dilated convolutions for medical image segmentation (SDU-Net).
no code implementations • 20 Mar 2020 • Szu-Yeu Hu, Shuhang Wang, Wei-Hung Weng, JingChao Wang, XiaoHong Wang, Arinc Ozturk, Qian Li, Viksit Kumar, Anthony E. Samir
Modern deep learning algorithms geared towards clinical adaption rely on a significant amount of high fidelity labeled data.