AIMC Topic: Whole Body Imaging
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A deep learning method for total-body dynamic PET imaging with dual-time-window protocols.
European journal of nuclear medicine and molecular imaging
Dec 17, 2024
PURPOSE: Prolonged scanning durations are one of the primary barriers to the widespread clinical adoption of dynamic Positron Emission Tomography (PET). In this paper, we developed a deep learning algorithm that capable of predicting dynamic images f...
Self-supervised neural network for Patlak-based parametric imaging in dynamic [F]FDG total-body PET.
European journal of nuclear medicine and molecular imaging
Dec 2, 2024
PURPOSE: The objective of this study is to generate reliable K parametric images from a shortened [F]FDG total-body PET for clinical applications using a self-supervised neural network algorithm.
Deep learning-based body composition analysis from whole-body magnetic resonance imaging to predict all-cause mortality in a large western population.
EBioMedicine
Dec 1, 2024
BACKGROUND: Manually extracted imaging-based body composition measures from a single-slice area (A) have shown associations with clinical outcomes in patients with cardiometabolic disease and cancer. With advances in artificial intelligence, fully au...
Personalized melanoma grading system: a presentation of a patient with four melanomas detected over two decades with evolving whole-body imaging and artificial intelligence systems.
Dermatology online journal
Oct 15, 2024
Melanoma is a life-threatening tumor that significantly impacts individuals' health and society worldwide. Therefore, its diagnostic tools must be revolutionized, representing the most remarkable human efforts toward successful management. This retro...
Total-Body PET/CT: A Role of Artificial Intelligence?
Seminars in nuclear medicine
Oct 5, 2024
The purpose of this paper is to provide an overview of the cutting-edge applications of artificial intelligence (AI) technology in total-body positron emission tomography/computed tomography (PET/CT) scanning technology and its profound impact on the...
Clinical performance of deep learning-enhanced ultrafast whole-body scintigraphy in patients with suspected malignancy.
BMC medical imaging
Sep 9, 2024
BACKGROUND: To evaluate the clinical performance of two deep learning methods, one utilizing real clinical pairs and the other utilizing simulated datasets, in enhancing image quality for two-dimensional (2D) fast whole-body scintigraphy (WBS).
Deep learning applications for quantitative and qualitative PET in PET/MR: technical and clinical unmet needs.
Magma (New York, N.Y.)
Aug 21, 2024
We aim to provide an overview of technical and clinical unmet needs in deep learning (DL) applications for quantitative and qualitative PET in PET/MR, with a focus on attenuation correction, image enhancement, motion correction, kinetic modeling, and...
Research Note: A deep learning method segments chicken keel bones from whole-body X-ray images.
Poultry science
Aug 13, 2024
Most commercial laying hens suffer from sternum (keel) bone damage including deviations and fractures. X-raying hens, followed by segmenting and assessing the keel bone, is a key to automating the monitoring of keel bone condition. The aim of the cur...
Association between myosteatosis and impaired glucose metabolism: A deep learning whole-body magnetic resonance imaging population phenotyping approach.
Journal of cachexia, sarcopenia and muscle
Jul 15, 2024
BACKGROUND: There is increasing evidence that myosteatosis, which is currently not assessed in clinical routine, plays an important role in risk estimation in individuals with impaired glucose metabolism, as it is associated with the progression of i...
Image quality of whole-body diffusion MR images comparing deep-learning accelerated and conventional sequences.
European radiology
Jul 4, 2024
OBJECTIVES: To compare the image quality of deep learning accelerated whole-body (WB) with conventional diffusion sequences.
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