Medical Object Detection On Deeplesion

Metrics

Sensitivity

Results

Performance results of various models on this benchmark

		Paper Title
P3D	88.55	Advancing 3D Medical Image Analysis with Variable Dimension Transform based Supervised 3D Pre-training
DKMA-ULD	87.16	DKMA-ULD: Domain Knowledge augmented Multi-head Attention based Robust Universal Lesion Detection
AlignShift	86.83	Conditional Training with Bounding Map for Universal Lesion Detection
MP3D	86.74	Revisiting 3D Context Modeling with Supervised Pre-training for Universal Lesion Detection in CT Slices
MELD	86.6	Universal Lesion Detection by Learning from Multiple Heterogeneously Labeled Datasets
FCOS	86.05	An Efficient Anchor-free Universal Lesion Detection in CT-scans
MULAN	85.22	MULAN: Multitask Universal Lesion Analysis Network for Joint Lesion Detection, Tagging, and Segmentation
MVP Net	83.64	MVP-Net: Multi-view FPN with Position-aware Attention for Deep Universal Lesion Detection
Improved RetinaNet	82.36	Improving RetinaNet for CT Lesion Detection with Dense Masks from Weak RECIST Labels
3DCE	75.55	3D Context Enhanced Region-based Convolutional Neural Network for End-to-End Lesion Detection

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Medical Object Detection On Deeplesion | SOTA | HyperAI