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SOTA
医学图像分割
Medical Image Segmentation On Bkai Igh
Medical Image Segmentation On Bkai Igh
评估指标
Average Dice
mIoU
评测结果
各个模型在此基准测试上的表现结果
Columns
模型名称
Average Dice
mIoU
Paper Title
Repository
TGANet
0.9023
0.8409
TGANet: Text-guided attention for improved polyp segmentation
-
ColonSegNet
0.6881
-
Real-Time Polyp Detection, Localization and Segmentation in Colonoscopy Using Deep Learning
-
QTSeg
-
-
QTSeg: A Query Token-Based Dual-Mix Attention Framework with Multi-Level Feature Distribution for Medical Image Segmentation
-
BlazeNeo
0.78802
-
BlazeNeo: Blazing fast polyp segmentation and neoplasm detection
-
FocalUNet
0.8021
-
Focal-UNet: UNet-like Focal Modulation for Medical Image Segmentation
-
NeoUNet
0.80723
-
NeoUNet: Towards accurate colon polyp segmentation and neoplasm detection
-
EMCAD
0.9296
-
EMCAD: Efficient Multi-scale Convolutional Attention Decoding for Medical Image Segmentation
-
TransResU-Net
0.9154
0.8568
TransResU-Net: Transformer based ResU-Net for Real-Time Colonoscopy Polyp Segmentation
-
RaBiT
0.94
0.886
RaBiT: An Efficient Transformer using Bidirectional Feature Pyramid Network with Reverse Attention for Colon Polyp Segmentation
-
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