Papers with Code 아카이브

Medical Object Detection

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하위 태스크: 0
평가표: 4
보존된 평가 기록: 14

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

<span style="color:grey; opacity: 0.6">( Image credit: Liver Lesion Detection from Weakly-labeled Multi-phase CT Volumes with a Grouped Single Shot MultiBox Detector )</span>

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/Zhang-Jing-Xuan/MaskRCNN

MULAN: Multitask Universal Lesion Analysis Network for Joint Lesion Detection, Tagging, and Segmentation

https://github.com/banben/maskrcnn-benchmark

MULAN: Multitask Universal Lesion Analysis Network for Joint Lesion Detection, Tagging, and Segmentation

https://github.com/basaltzhang/maskrcnn-benchmark

MULAN: Multitask Universal Lesion Analysis Network for Joint Lesion Detection, Tagging, and Segmentation

https://github.com/ccchang1023/maskrcnn-benchmark

MULAN: Multitask Universal Lesion Analysis Network for Joint Lesion Detection, Tagging, and Segmentation

https://github.com/chenxd2/Detecting-Cancer-Metastases-on-Gigapixel-Pathology-Images

Detecting Cancer Metastases on Gigapixel Pathology Images

https://github.com/cyctrung/DPnet

MULAN: Multitask Universal Lesion Analysis Network for Joint Lesion Detection, Tagging, and Segmentation

https://github.com/fizyr/keras-retinanet

Improving RetinaNet for CT Lesion Detection with Dense Masks from Weak RECIST Labels

https://github.com/fsafe/Capstone

3D Context Enhanced Region-based Convolutional Neural Network for End-to-End Lesion Detection

https://github.com/ivanwilliammd/I3DR-Net-Transfer-Learning

Retina U-Net: Embarrassingly Simple Exploitation of Segmentation Supervision for Medical Object Detection

https://github.com/jonvthvn90/Project

MULAN: Multitask Universal Lesion Analysis Network for Joint Lesion Detection, Tagging, and Segmentation

https://github.com/kira-95/adl_cancer_detection

Detecting Cancer Metastases on Gigapixel Pathology Images

https://github.com/leeh43/Singularity_Deeplesion

MULAN: Multitask Universal Lesion Analysis Network for Joint Lesion Detection, Tagging, and Segmentation

https://github.com/markson14/WheatDet

MULAN: Multitask Universal Lesion Analysis Network for Joint Lesion Detection, Tagging, and Segmentation

https://github.com/martinzlocha/anchor-optimization

Improving RetinaNet for CT Lesion Detection with Dense Masks from Weak RECIST Labels

https://github.com/olahosa/adl_cancer_detection

Detecting Cancer Metastases on Gigapixel Pathology Images

https://github.com/remydubois/lsnms

Retina U-Net: Embarrassingly Simple Exploitation of Segmentation Supervision for Medical Object Detection

https://github.com/ryota2425/maskrcnn-benchmark

MULAN: Multitask Universal Lesion Analysis Network for Joint Lesion Detection, Tagging, and Segmentation

https://github.com/truetqy/lesion_det_dual_att

3D Context Enhanced Region-based Convolutional Neural Network for End-to-End Lesion Detection

https://github.com/virabehnam/CAMELYON16-Breast-Cancer-Detection

Detecting Cancer Metastases on Gigapixel Pathology Images

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.