https://github.com/rohitrango/Magic-or-Mirage
공식 코드Deep Learning in Medical Image Registration: Magic or Mirage?
Papers with Code 아카이브
Image Registration
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 2
- 평가표
- 5
- 보존된 평가 기록
- 22
Image registration is the process of transforming different sets of data into one coordinate system. Data may be multiple photographs, data from different sensors, times, depths, or viewpoints. It is used in computer vision, medical imaging, and compiling and analyzing images and data from satellites. Registration is necessary in order to be able to compare or integrate the data obtained from these different measurements.
Source: Image registration | Wikipedia
( Image credit: Kornia )
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/rohitrango/dio
공식 코드Deep Implicit Optimization enables Robust Learnable Features for Deformable Image Registration
https://github.com/rohitrango/fireants
공식 코드FireANTs: Adaptive Riemannian Optimization for Multi-Scale Diffeomorphic Matching
https://github.com/roland1993/d_RPCA
공식 코드Deformable Groupwise Image Registration using Low-Rank and Sparse Decomposition
https://github.com/rousseau/dynMRI
공식 코드https://github.com/rtaiello/pp_dipy
공식 코드https://github.com/rtaiello/pp_image_registration
공식 코드https://github.com/ruc-aimc-lab/superretina
공식 코드Semi-Supervised Keypoint Detector and Descriptor for Retinal Image Matching
https://github.com/ruizhe-l/mrregnet
공식 코드https://github.com/runshi-zhang/utsrmorph
공식 코드https://github.com/rvimlab/h_rcm_vs_ws
공식 코드https://github.com/rvimlab/homography_imitation_learning
공식 코드Deep Homography Prediction for Endoscopic Camera Motion Imitation Learning
https://github.com/saalfeldlab/bigwarp
공식 코드Robust Registration of Calcium Images by Learned Contrast Synthesis
https://github.com/samahkh/npbdreg_prj
공식 코드https://github.com/shangwei5/selfdrsc_plusplus
공식 코드SelfDRSC++: Self-Supervised Learning for Dual Reversed Rolling Shutter Correction
https://github.com/shaoyanpan/Synthetic-CT-generation-from-MRI-using-3D-transformer-based-denoising-diffusion-model
공식 코드Synthetic CT Generation from MRI using 3D Transformer-based Denoising Diffusion Model
https://github.com/simbauer/to_glue_or_not_to_glue
공식 코드https://github.com/singhay/DeepPredictiveMotionTracking
공식 코드Deep Predictive Motion Tracking in Magnetic Resonance Imaging: Application to Fetal Imaging
https://github.com/singnet/image-matching
공식 코드GoodPoint: unsupervised learning of keypoint detection and description
https://github.com/solemoon/xmorpher
공식 코드XMorpher: Full Transformer for Deformable Medical Image Registration via Cross Attention
https://github.com/soumickmj/micdir
공식 코드https://github.com/soumyadeep-pal/diffeomorphic-image-registration-postprocess
공식 코드https://github.com/sqhuang0103/samreg
공식 코드https://github.com/stefhk3/nmrchemclassify
공식 코드https://github.com/stergioc/smooth-transformer
공식 코드Linear and Deformable Image Registration with 3D Convolutional Neural Networks
https://github.com/suuujm/spss
공식 코드Self-Paced Sample Selection for Barely-Supervised Medical Image Segmentation
https://github.com/tadsgroup/kernelodetransport
공식 코드Diffeomorphic Measure Matching with Kernels for Generative Modeling
https://github.com/tanguymagne/uvdoc
공식 코드https://github.com/technioncomputationalmrilab/mbss-t1
공식 코드https://github.com/technioncomputationalmrilab/qdwi-morph
공식 코드https://github.com/thomasbudd/ctarr
공식 코드https://github.com/tinymilky/deda
공식 코드https://github.com/tinymilky/mem-warp
공식 코드MemWarp: Discontinuity-Preserving Cardiac Registration with Memorized Anatomical Filters
https://github.com/toros-astro/astroalign
공식 코드Astroalign: A Python module for astronomical image registration
https://github.com/tuffr5/saner-deep-registration
공식 코드https://github.com/uncbiag/ByConstructionICON
공식 코드Inverse Consistency by Construction for Multistep Deep Registration
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.