AIMC Topic: Tomography, X-Ray Computed
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Dynamic Loss Weighting for Multiorgan Segmentation in Medical Images.
IEEE transactions on neural networks and learning systems
Aug 5, 2024
Deep neural networks often suffer from performance inconsistency for multiorgan segmentation in medical images; some organs are segmented far worse than others. The main reason might be organs with different levels of learning difficulty for segmenta...
Performance of AI for preoperative CT assessment of lung metastases: Retrospective analysis of 167 patients.
European journal of radiology
Aug 3, 2024
OBJECTIVES: To evaluate the performance of artificial intelligence (AI) in the preoperative detection of lung metastases on CT.
Automated segmentation in pelvic radiotherapy: A comprehensive evaluation of ATLAS-, machine learning-, and deep learning-based models.
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)
Aug 3, 2024
Artificial intelligence can standardize and automatize highly demanding procedures, such as manual segmentation, especially in an anatomical site as common as the pelvis. This study investigated four automated segmentation tools on computed tomograph...
Estimating three-dimensional foot bone kinematics from skin markers using a deep learning neural network model.
Journal of biomechanics
Aug 3, 2024
The human foot is a complex structure comprising 26 bones, whose coordinated movements facilitate proper deformation of the foot, ensuring stable and efficient locomotion. Despite their critical role, the kinematics of foot bones during movement rema...
Effect of Deep Learning Image Reconstruction Algorithms on Radiomic Features of Pulmonary Nodules in Ultra-Low-Dose CT.
Journal of computer assisted tomography
Aug 2, 2024
OBJECTIVE: The purpose of this study is to explore the impact of deep learning image reconstruction (DLIR) algorithm on the quantification of radiomic features in ultra-low-dose computed tomography (ULD-CT) compared with adaptive statistical iterativ...
Structure and position-aware graph neural network for airway labeling.
Medical image analysis
Aug 2, 2024
We present a novel graph-based approach for labeling the anatomical branches of a given airway tree segmentation. The proposed method formulates airway labeling as a branch classification problem in the airway tree graph, where branch features are ex...
Intelligent skin-removal photoacoustic computed tomography for human based on deep learning.
Journal of biophotonics
Aug 2, 2024
Photoacoustic computed tomography (PACT) has centimeter-level imaging ability and can be used to detect the human body. However, strong photoacoustic signals from skin cover deep tissue information, hindering the frontal display and analysis of photo...
Enhancing Outcome Prediction in Intracerebral Hemorrhage Through Deep Learning: A Retrospective Multicenter Study.
Academic radiology
Aug 1, 2024
RATIONALE AND OBJECTIVES: This study aimed to employ deep learning techniques to analyze and validate an automatic prognostic biomarker for predicting outcomes following intracerebral hemorrhage (ICH).
Development of a CT-Based comprehensive model combining clinical, radiomics with deep learning for differentiating pulmonary metastases from noncalcified pulmonary hamartomas: a retrospective cohort study.
International journal of surgery (London, England)
Aug 1, 2024
BACKGROUND: Clinical differentiation between pulmonary metastases and noncalcified pulmonary hamartomas (NCPH) often presents challenges, leading to potential misdiagnosis. However, the efficacy of a comprehensive model that integrates clinical featu...
A commentary on 'A CT-based deep learning model predicts overall survival in patients with muscle invasive bladder cancer after radical cystectomy: a multicenter retrospective cohort study'.
International journal of surgery (London, England)
Aug 1, 2024
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