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20152022
most citedTransUNet: Transformers Make Strong Encoders for Medical Image Segmentation

4k citations · 5.2k across the 49 of their papers we have counts for

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cs.CV20211 cited

Multi-institutional Validation of Two-Streamed Deep Learning Method for Automated Delineation of Esophageal Gross Tumor Volume using planning-CT and FDG-PETCT

Xianghua Ye, Dazhou Guo, Chen-kan Tseng +22

Background: The current clinical workflow for esophageal gross tumor volume (GTV) contouring relies on manual delineation of high labor-costs and interuser variability. Purpose: To…

cs.CV2021

Scalable Semi-supervised Landmark Localization for X-ray Images using Few-shot Deep Adaptive Graph

Xiao-Yun Zhou, Bolin Lai, Weijian Li +12

Landmark localization plays an important role in medical image analysis. Learning based methods, including CNN and GCN, have demonstrated the state-of-the-art performance. However,…

cs.CV2021

Learning from Subjective Ratings Using Auto-Decoded Deep Latent Embeddings

Bowen Li, Xinping Ren, Ke Yan +6

Depending on the application, radiological diagnoses can be associated with high inter- and intra-rater variabilities. Most computer-aided diagnosis (CAD) solutions treat such data…

cs.CV2021

Hetero-Modal Learning and Expansive Consistency Constraints for Semi-Supervised Detection from Multi-Sequence Data

Bolin Lai, Yuhsuan Wu, Xiao-Yun Zhou +7

Lesion detection serves a critical role in early diagnosis and has been well explored in recent years due to methodological advancesand increased data availability. However, the hi…

cs.CV20214k cited

TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation

Jieneng Chen, Yongyi Lu, Qihang Yu +6

Medical image segmentation is an essential prerequisite for developing healthcare systems, especially for disease diagnosis and treatment planning. On various medical image segment…

cs.CV20217 cited

A New Window Loss Function for Bone Fracture Detection and Localization in X-ray Images with Point-based Annotation

Xinyu Zhang, Yirui Wang, Chi-Tung Cheng +5

Object detection methods are widely adopted for computer-aided diagnosis using medical images. Anomalous findings are usually treated as objects that are described by bounding boxe…