Papers with Code 아카이브

Medical Image Registration

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

하위 태스크
2
평가표
4
보존된 평가 기록
18

Image registration, also known as image fusion or image matching, is the process of aligning two or more images based on image appearances. Medical Image Registration seeks to find an optimal spatial transformation that best aligns the underlying anatomical structures. Medical Image Registration is used in many clinical applications such as image guidance, motion tracking, segmentation, dose accumulation, image reconstruction and so on. Medical Image Registration is a broad topic which can be grouped from various perspectives. From input image point of view, registration methods can be divided into unimodal, multimodal, interpatient, intra-patient (e.g. same- or different-day) registration. From deformation model point of view, registration methods can be divided in to rigid, affine and deformable methods. From region of interest (ROI) perspective, registration methods can be grouped according to anatomical sites such as brain, lung registration and so on. From image pair dimension perspective, registration methods can be divided into 3D to 3D, 3D to 2D and 2D to 2D/3D.

Source: Deep Learning in Medical Image Registration: A Review

평가 결과

데이터셋과 평가 조건을 선택해 성능·논문·코드를 비교하세요. 보존된 Papers with Code 기록으로, 최신 순위는 아닙니다.

IXI

원본 태스크: Medical Image Registration

평가 기록 8건

OASIS

원본 태스크: Medical Image Registration

평가 기록 8건

CIMA-10k

원본 태스크: Medical Image Registration / BIRL

평가 기록 3건

CUMC12

원본 태스크: Medical Image Registration / Diffeomorphic Medical Image Registration

평가 기록 3건

SR-Reg

원본 태스크: Medical Image Registration

평가 기록 1건

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