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Computed Tomography (CT)

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The term “computed tomography”, or CT, refers to a computerized x-ray imaging procedure in which a narrow beam of x-rays is aimed at a patient and quickly rotated around the body, producing signals that are processed by the machine's computer to generate cross-sectional images—or “slices”—of the body.

<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/nspunn1993/COVID-19-PA-CXR-fused-dataset

공식 코드

Automated diagnosis of COVID-19 with limited posteroanterior chest X-ray images using fine-tuned deep neural networks

https://github.com/plantonsanti/PartialMatchingVarifolds

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How to Register a Live onto a Liver ? Partial Matching in the Space of Varifolds

https://github.com/poiuohke/UDC-Net

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Dual-Consistency Semi-Supervised Learning with Uncertainty Quantification for COVID-19 Lesion Segmentation from CT Images

https://github.com/pragyanstha/scr-registration

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X-Ray to CT Rigid Registration Using Scene Coordinate Regression

https://github.com/project-lighter/lighter

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Vision Foundation Models for Computed Tomography

https://github.com/qgao21/corediff

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CoreDiff: Contextual Error-Modulated Generalized Diffusion Model for Low-Dose CT Denoising and Generalization

https://github.com/qgking/FRGAN

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Free-form tumor synthesis in computed tomography images via richer generative adversarial network

https://github.com/qibaolian/ctn

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Deep 3D Vessel Segmentation based on Cross Transformer Network

https://github.com/qjy415417122/sa-roundtrip

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Bayesian imaging inverse problem with SA-Roundtrip prior via HMC-pCN sampler

https://github.com/quan14/AirwayTaperingInCT

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Tapering Analysis of Airways with Bronchiectasis

https://github.com/rachellea/ct-net-models

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Machine-Learning-Based Multiple Abnormality Prediction with Large-Scale Chest Computed Tomography Volumes

https://github.com/ristea/cycle-transformer

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CyTran: A Cycle-Consistent Transformer with Multi-Level Consistency for Non-Contrast to Contrast CT Translation

https://github.com/rmf3mc/covid-comp24

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COVID-19 detection from pulmonary CT scans using a novel EfficientNet with attention mechanism

https://github.com/ronenroi/4D-Cloud-Scattering-Tomography

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Spatiotemporal tomography based on scattered multiangular signals and its application for resolving evolving clouds using moving platforms

https://github.com/rongzhao-zhang/ag-crc

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AG-CRC: Anatomy-Guided Colorectal Cancer Segmentation in CT with Imperfect Anatomical Knowledge

https://github.com/rsummers11/CADLab

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Anatomy-specific classification of medical images using deep convolutional nets

https://github.com/ruishengsu/2.75d

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2.75D: Boosting learning by representing 3D Medical imaging to 2D features for small data

https://github.com/ruixxxx/lssanet

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LSSANet: A Long Short Slice-Aware Network for Pulmonary Nodule Detection

https://github.com/rvignav/CT2Xray

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COVID-19 Lung Lesion Segmentation Using a Sparsely Supervised Mask R-CNN on Chest X-rays Automatically Computed from Volumetric CTs

https://github.com/samleoqh/viola-unet

공식 코드

Voxels Intersecting along Orthogonal Levels Attention U-Net for Intracerebral Haemorrhage Segmentation in Head CT

https://github.com/sandialabs/bcnn

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We Know Where We Don't Know: 3D Bayesian CNNs for Credible Geometric Uncertainty

https://github.com/sebastienlinker/eit_post_processing

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A Post-Processing Tool and Feasibility Study for Three-Dimensional Imaging with Electrical Impedance Tomography During Deep Brain Stimulation Surgery

https://github.com/sedaboni/PnP-TV

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Plug-and-Play gradient-based denoisers applied to CT image enhancement

https://github.com/sedaboni/TomoSelfDEQ

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TomoSelfDEQ: Self-Supervised Deep Equilibrium Learning for Sparse-Angle CT Reconstruction

https://github.com/sepidehamiri/pet_seg_unet

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Improved automated lesion segmentation in whole-body FDG/PET-CT via Test-Time Augmentation

https://github.com/shijun18/COVID-19_CLS

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DARNet: Dual-Attention Residual Network for Automatic Diagnosis of COVID-19 via CT Images

https://github.com/shizenglin/Frequency-Supervised-MR-to-CT-Image-Synthesis

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Frequency-Supervised MR-to-CT Image Synthesis

https://github.com/shruti-jadon/Brain-Lesions-Segmentation

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A comparative study of 2D image segmentation algorithms for traumatic brain lesions using CT data from the ProTECTIII multicenter clinical trial

https://github.com/shuaichenbigr/label-refinement-network

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Label Refinement Network from Synthetic Error Augmentation for Medical Image Segmentation

https://github.com/shubhamchaudhary2015/ct_covid19_cap_cnn

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Detecting COVID-19 and Community Acquired Pneumonia using Chest CT scan images with Deep Learning

https://github.com/simontomaskarlsson/GAN-MRI

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Generative Adversarial Networks for Image-to-Image Translation on Multi-Contrast MR Images - A Comparison of CycleGAN and UNIT

https://github.com/smg478/OralCancerDetectionOnCTImages

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Computer Aided Detection of Oral Lesions on CT Images

https://github.com/stanfordmimi/comp2comp

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Comp2Comp: Open-Source Body Composition Assessment on Computed Tomography

https://github.com/staruniversus/gcmae

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Global Contrast Masked Autoencoders Are Powerful Pathological Representation Learners

https://github.com/stefenmax/PSDM

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Physics-informed Score-based Diffusion Model for Limited-angle Reconstruction of Cardiac Computed Tomography

https://github.com/sulam-group/k-rcps

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How to Trust Your Diffusion Model: A Convex Optimization Approach to Conformal Risk Control

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