AutoCT: Automated CT registration, segmentation, and quantification
The processing and analysis of computed tomography (CT) imaging is important for both basic scientific development and clinical applications. In AutoCT, we provide a comprehensive pipeline that integrates an end-to-end automatic preprocessing, registration, segmentation, and quantitative analysis of 3D CT scans. The engineered pipeline enables atlas-based CT segmentation and quantification leveraging diffeomorphic transformations through efficient forward and inverse mappings. The extracted localized features from the deformation field allow for downstream statistical learning that may facilitate medical diagnostics. On a lightweight and portable software platform, AutoCT provides a new toolkit for the CT imaging community to underpin the deployment of artificial intelligence-driven applications.
Code (0)
등록된 구현이 없습니다.
Tasks
Computed Tomography (CT)SegmentationSimilar Papers 제목 키워드 기반
Deep learning facilitates fully automated brain image registration of optoacoustic tomography and magnetic resonance imaging
Multi-spectral optoacoustic tomography (MSOT) is an emerging optical imaging method providing multiplex molecular and functional information from the rodent brain. It can be greatly augmented by magnetic resonance imagin…
AnatomyBrain SegmentationImage RegistrationImage Segmentation+2AutoCTS: Automated Correlated Time Series Forecasting -- Extended Version
Correlated time series (CTS) forecasting plays an essential role in many cyber-physical systems, where multiple sensors emit time series that capture interconnected processes. Solutions based on deep learning that delive…
Correlated Time Series ForecastingTime SeriesTime Series AnalysisTime Series ForecastingTowards Automated Neural Interaction Discovery for Click-Through Rate Prediction
Click-Through Rate (CTR) prediction is one of the most important machine learning tasks in recommender systems, driving personalized experience for billions of consumers. Neural architecture search (NAS), as an emerging …
Click-Through Rate PredictionLearning-To-RankNeural Architecture SearchRecommendation SystemsAutomated Atlas-based Segmentation of Single Coronal Mouse Brain Slices using Linear 2D-2D Registration
A significant challenge for brain histological data analysis is to precisely identify anatomical regions in order to perform accurate local quantifications and evaluate therapeutic solutions. Usually, this task is perfor…
SegmentationCMRINet: Joint Groupwise Registration and Segmentation for Cardiac Function Quantification from Cine-MRI
Accurate and efficient quantification of cardiac function is essential for the estimation of prognosis of cardiovascular diseases (CVDs). One of the most commonly used metrics for evaluating cardiac pumping performance i…
Prognosis