Search Results for author: Shang Zhao

Found 8 papers, 0 papers with code

Unsupervised augmentation optimization for few-shot medical image segmentation

no code implementations8 Jun 2023 Quan Quan, Shang Zhao, Qingsong Yao, Heqin Zhu, S. Kevin Zhou

The augmentation parameters matter to few-shot semantic segmentation since they directly affect the training outcome by feeding the networks with varying perturbated samples.

Anatomy Few-Shot Semantic Segmentation +3

GDDS: Pulmonary Bronchioles Segmentation with Group Deep Dense Supervision

no code implementations16 Mar 2023 Mingyue Zhao, Shang Zhao, Quan Quan, Li Fan, Xiaolan Qiu, Shiyuan Liu, S. Kevin Zhou

To address these problems, we contribute a new bronchial segmentation method based on Group Deep Dense Supervision (GDDS) that emphasizes fine-scale bronchioles segmentation in a simple-but-effective manner.

FairAdaBN: Mitigating unfairness with adaptive batch normalization and its application to dermatological disease classification

no code implementations15 Mar 2023 Zikang Xu, Shang Zhao, Quan Quan, Qingsong Yao, S. Kevin Zhou

Deep learning is becoming increasingly ubiquitous in medical research and applications while involving sensitive information and even critical diagnosis decisions.


MURPHY: Relations Matter in Surgical Workflow Analysis

no code implementations24 Dec 2022 Shang Zhao, Yanzhe Liu, Qiyuan Wang, Dai Sun, Rong Liu, S. Kevin Zhou

Autonomous robotic surgery has advanced significantly based on analysis of visual and temporal cues in surgical workflow, but relational cues from domain knowledge remain under investigation.

Active CT Reconstruction with a Learned Sampling Policy

no code implementations3 Nov 2022 Ce Wang, Kun Shang, Haimiao Zhang, Shang Zhao, Dong Liang, S. Kevin Zhou

Experiments on the VerSe dataset demonstrate this ability of our sampling policy, which is difficult to achieve based on uniform sampling.

Computed Tomography (CT) Decision Making

3D endoscopic depth estimation using 3D surface-aware constraints

no code implementations4 Mar 2022 Shang Zhao, Ce Wang, Qiyuan Wang, Yanzhe Liu, S Kevin Zhou

We propose a loss function for depth estimation that integrates the surface-aware constraints, leading to a faster and better convergence with the valid information from spatial information.

Depth Estimation Image Reconstruction

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