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Medical Object Detection On Deeplesion

Metrics

Sensitivity

Results

Performance results of various models on this benchmark

Model Name
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
0 of 10 row(s) selected.
Medical Object Detection On Deeplesion | SOTA | HyperAI