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홈뉴스최신 연구 논문튜토리얼데이터셋백과사전SOTALLM 모델GPU 랭킹컨퍼런스
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  4. Medical Object Detection On Deeplesion

Medical Object Detection On Deeplesion

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이 벤치마크에서 각 모델의 성능 결과

모델 이름
Sensitivity
Paper TitleRepository
P3D88.55Advancing 3D Medical Image Analysis with Variable Dimension Transform based Supervised 3D Pre-training
MELD86.6Universal Lesion Detection by Learning from Multiple Heterogeneously Labeled Datasets-
Improved RetinaNet82.36Improving RetinaNet for CT Lesion Detection with Dense Masks from Weak RECIST Labels
MVP Net83.64MVP-Net: Multi-view FPN with Position-aware Attention for Deep Universal Lesion Detection
FCOS86.05An Efficient Anchor-free Universal Lesion Detection in CT-scans-
AlignShift86.83Conditional Training with Bounding Map for Universal Lesion Detection-
MULAN85.22MULAN: Multitask Universal Lesion Analysis Network for Joint Lesion Detection, Tagging, and Segmentation
DKMA-ULD87.16DKMA-ULD: Domain Knowledge augmented Multi-head Attention based Robust Universal Lesion Detection-
MP3D86.74Revisiting 3D Context Modeling with Supervised Pre-training for Universal Lesion Detection in CT Slices
3DCE75.553D Context Enhanced Region-based Convolutional Neural Network for End-to-End Lesion Detection
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