AIMC Topic: Whole Body Imaging
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Development and validation of pan-cancer lesion segmentation AI-model for whole-body 18F-FDG PET/CT in diverse clinical cohorts.
Computers in biology and medicine
Mar 23, 2025
BACKGROUND: This study develops a deep learning-based automated lesion segmentation model for whole-body 3DF-fluorodeoxyglucose (FDG)-Position emission tomography (PET) with computed tomography (CT) images agnostic to disease location and site.
HybrIK-X: Hybrid Analytical-Neural Inverse Kinematics for Whole-Body Mesh Recovery.
IEEE transactions on pattern analysis and machine intelligence
Mar 6, 2025
Recovering whole-body mesh by inferring the abstract pose and shape parameters from visual content can obtain 3D bodies with realistic structures. However, the inferring process is highly non-linear and suffers from image-mesh misalignment, resulting...
Automatic detecting multiple bone metastases in breast cancer using deep learning based on low-resolution bone scan images.
Scientific reports
Mar 6, 2025
Whole-body bone scan (WBS) is usually used as the effective diagnostic method for early-stage and comprehensive bone metastases of breast cancer. WBS images with breast cancer bone metastasis have the characteristics of low resolution, small foregrou...
Robust and generalizable artificial intelligence for multi-organ segmentation in ultra-low-dose total-body PET imaging: a multi-center and cross-tracer study.
European journal of nuclear medicine and molecular imaging
Feb 19, 2025
PURPOSE: Positron Emission Tomography (PET) is a powerful molecular imaging tool that visualizes radiotracer distribution to reveal physiological processes. Recent advances in total-body PET have enabled low-dose, CT-free imaging; however, accurate o...
Comparative analysis of intestinal tumor segmentation in PET CT scans using organ based and whole body deep learning.
BMC medical imaging
Feb 17, 2025
BACKGROUND: 18-Fluoro-deoxyglucose positron emission tomography/computed tomography (FDG-PET/CT) is a valuable imaging tool widely used in the management of cancer patients. Deep learning models excel at segmenting highly metabolic tumors but face ch...
Eliminating the second CT scan of dual-tracer total-body PET/CT via deep learning-based image synthesis and registration.
European journal of nuclear medicine and molecular imaging
Feb 11, 2025
PURPOSE: This study aims to develop and validate a deep learning framework designed to eliminate the second CT scan of dual-tracer total-body PET/CT imaging.
CT-Less Whole-Body Bone Segmentation of PET Images Using a Multimodal Deep Learning Network.
IEEE journal of biomedical and health informatics
Feb 10, 2025
In bone cancer imaging, positron emission tomography (PET) is ideal for the diagnosis and staging of bone cancers due to its high sensitivity to malignant tumors. The diagnosis of bone cancer requires tumor analysis and localization, where accurate a...
Development and validation of fully automated robust deep learning models for multi-organ segmentation from whole-body CT images.
Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
Feb 2, 2025
PURPOSE: This study aimed to develop a deep-learning framework to generate multi-organ masks from CT images in adult and pediatric patients.
Non-parametric Bayesian deep learning approach for whole-body low-dose PET reconstruction and uncertainty assessment.
Medical & biological engineering & computing
Jan 23, 2025
Positron emission tomography (PET) imaging plays a pivotal role in oncology for the early detection of metastatic tumors and response to therapy assessment due to its high sensitivity compared to anatomical imaging modalities. The balance between ima...
Evaluation of a Deep Learning Denoising Algorithm for Dose Reduction in Whole-Body Photon-Counting CT Imaging: A Cadaveric Study.
Academic radiology
Jan 15, 2025
RATIONALE AND OBJECTIVES: Photon Counting CT (PCCT) offers advanced imaging capabilities with potential for substantial radiation dose reduction; however, achieving this without compromising image quality remains a challenge due to increased noise at...
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