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20162023
most citedTransUNet: Transformers Make Strong Encoders for Medical Image Segmentation

4k citations · 4.6k across the 25 of their papers we have counts for

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Showing 2019Show all

7 papers · 1 filter

cs.CV2019★ 7 cited

Deep Distance Transform for Tubular Structure Segmentation in CT Scans

Yan Wang, Xu Wei, Fengze Liu +5

Tubular structure segmentation in medical images, e.g., segmenting vessels in CT scans, serves as a vital step in the use of computers to aid in screening early stages of related d…

eess.IV2019

Hyper-Pairing Network for Multi-Phase Pancreatic Ductal Adenocarcinoma Segmentation

Yuyin Zhou, Yingwei Li, Zhishuai Zhang +5

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers with an overall five-year survival rate of 8%. Due to subtle texture changes of PDAC, pancreatic dual-phas…

cs.CV2019

Universal Physical Camouflage Attacks on Object Detectors

Lifeng Huang, Chengying Gao, Yuyin Zhou +4

In this paper, we study physical adversarial attacks on object detectors in the wild. Previous works mostly craft instance-dependent perturbations only for rigid or planar objects.…

cs.CV2019

FusionNet: Incorporating Shape and Texture for Abnormality Detection in 3D Abdominal CT Scans

Fengze Liu, Yuyin Zhou, Elliot Fishman +1

Automatic abnormality detection in abdominal CT scans can help doctors improve the accuracy and efficiency in diagnosis. In this paper we aim at detecting pancreatic ductal adenoca…

eess.IV2019

Multi-Scale Attentional Network for Multi-Focal Segmentation of Active Bleed after Pelvic Fractures

Yuyin Zhou, David Dreizin, Yingwei Li +3

Trauma is the worldwide leading cause of death and disability in those younger than 45 years, and pelvic fractures are a major source of morbidity and mortality. Automated segmenta…

cs.CV2019

Prior-aware Neural Network for Partially-Supervised Multi-Organ Segmentation

Yuyin Zhou, Zhe Li, Song Bai +5

Accurate multi-organ abdominal CT segmentation is essential to many clinical applications such as computer-aided intervention. As data annotation requires massive human labor from…