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Medical Object Detection

Medical object detection is the task of identifying medical-based objects within an image.

( Image credit: Liver Lesion Detection from Weakly-labeled Multi-phase CT Volumes with a Grouped Single Shot MultiBox Detector )

Papers

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Showing 11–20 of 41 papers

TitleStatusHype
Fracture Detection in Pediatric Wrist Trauma X-ray Images Using YOLOv8 AlgorithmCode1
DeGPR: Deep Guided Posterior Regularization for Multi-Class Cell Detection and CountingCode1
RCS-YOLO: A Fast and High-Accuracy Object Detector for Brain Tumor DetectionCode1
Liver Lesion Detection from Weakly-labeled Multi-phase CT Volumes with a Grouped Single Shot MultiBox DetectorCode1
BGF-YOLO: Enhanced YOLOv8 with Multiscale Attentional Feature Fusion for Brain Tumor DetectionCode1
nnDetection: A Self-configuring Method for Medical Object DetectionCode1
Retina U-Net: Embarrassingly Simple Exploitation of Segmentation Supervision for Medical Object DetectionCode1
CircleFormer: Circular Nuclei Detection in Whole Slide Images with Circle Queries and AttentionCode1
DKMA-ULD: Domain Knowledge augmented Multi-head Attention based Robust Universal Lesion Detection—0
Accurate Detection of Mediastinal Lesions with nnDetection—0
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