14 citations · 41 across the 8 of their papers we have counts for
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SA-Med2D-20M Dataset: Segment Anything in 2D Medical Imaging with 20 Million masks
Jin Ye, Junlong Cheng, Jianpin Chen +12
Segment Anything Model (SAM) has achieved impressive results for natural image segmentation with input prompts such as points and bounding boxes. Its success largely owes to massiv…
Exploring Vanilla U-Net for Lesion Segmentation from Whole-body FDG-PET/CT Scans
Jin Ye, Haoyu Wang, Ziyan Huang +8
Tumor lesion segmentation is one of the most important tasks in medical image analysis. In clinical practice, Fluorodeoxyglucose Positron-Emission Tomography~(FDG-PET) is a widely…
An evaluation of U-Net in Renal Structure Segmentation
Haoyu Wang, Ziyan Huang, Jin Ye +7
Renal structure segmentation from computed tomography angiography~(CTA) is essential for many computer-assisted renal cancer treatment applications. Kidney PArsing~(KiPA 2022) Chal…
A Novel Hybrid Convolutional Neural Network for Accurate Organ Segmentation in 3D Head and Neck CT Images
Zijie Chen, Cheng Li, Junjun He +5
Radiation therapy (RT) is widely employed in the clinic for the treatment of head and neck (HaN) cancers. An essential step of RT planning is the accurate segmentation of various o…
Group Shift Pointwise Convolution for Volumetric Medical Image Segmentation
Junjun He, Jin Ye, Cheng Li +5
Recent studies have witnessed the effectiveness of 3D convolutions on segmenting volumetric medical images. Compared with the 2D counterparts, 3D convolutions can capture the spati…