AIMC Topic: Tomography, X-Ray Computed
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Machine learning-based CT radiomics approach for predicting occult peritoneal metastasis in advanced gastric cancer preoperatively.
Clinical radiology
Oct 18, 2024
AIM: To develop a machine learning-based CT radiomics model to preoperatively diagnose occult peritoneal metastasis (OPM) in advanced gastric cancer (AGC) patients.
Achieving accurate prostate auto-segmentation on CT in the absence of MR imaging.
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Oct 16, 2024
BACKGROUND: Magnetic resonance imaging (MRI) is considered the gold standard for prostate segmentation. Computed tomography (CT)-based segmentation is prone to observer bias, potentially overestimating the prostate volume by ∼ 30 % compared to MRI. H...
Deep convolutional neural network for automatic segmentation and classification of jaw tumors in contrast-enhanced computed tomography images.
International journal of oral and maxillofacial surgery
Oct 15, 2024
The purpose of this study was to evaluate the performance of convolutional neural network (CNN)-based image segmentation models for segmentation and classification of benign and malignant jaw tumors in contrast-enhanced computed tomography (CT) image...
Coronary artery calcium measurement on attenuation correction computed tomography using artificial intelligence: correlation with coronary flow capacity and prognosis.
European journal of nuclear medicine and molecular imaging
Oct 15, 2024
PURPOSE: This study aimed to test whether the coronary artery calcium (CAC) burden on attenuation correction computed tomography (CTac), measured using artificial intelligence (AI-CACac), correlates with coronary flow capacity (CFC) and prognosis.
Artificial Intelligence-Based Assessment of Preoperative Body Composition Is Associated With Early Complications After Radical Cystectomy.
The Journal of urology
Oct 11, 2024
PURPOSE: We aimed to use a validated artificial intelligence (AI) algorithm to extract muscle and adipose areas from CT images before radical cystectomy (RCx) and then correlate these measures with 90-day post-RCx complications.
An anthropomorphic diagnosis system of pulmonary nodules using weak annotation-based deep learning.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Oct 10, 2024
The accurate categorization of lung nodules in CT scans is an essential aspect in the prompt detection and diagnosis of lung cancer. The categorization of grade and texture for nodules is particularly significant since it can aid radiologists and cli...
Hyperparameter selection for dataset-constrained semantic segmentation: Practical machine learning optimization.
Journal of applied clinical medical physics
Oct 10, 2024
PURPOSE/AIM: This paper provides a pedagogical example for systematic machine learning optimization in small dataset image segmentation, emphasizing hyperparameter selections. A simple process is presented for medical physicists to examine hyperparam...
Deep learning from head CT scans to predict elevated intracranial pressure.
Journal of neuroimaging : official journal of the American Society of Neuroimaging
Oct 10, 2024
BACKGROUND AND PURPOSE: Elevated intracranial pressure (ICP) resulting from severe head injury or stroke poses a risk of secondary brain injury that requires neurosurgical intervention. However, currently available noninvasive monitoring techniques f...
Dual Energy CT for Deep Learning-Based Segmentation and Volumetric Estimation of Early Ischemic Infarcts.
Journal of imaging informatics in medicine
Oct 9, 2024
Ischemic changes are not visible on non-contrast head CT until several hours after infarction, though deep convolutional neural networks have shown promise in the detection of subtle imaging findings. This study aims to assess if dual-energy CT (DECT...
Implementation of an AI Algorithm in Clinical Practice to Reduce Missed Incidental Pulmonary Embolisms on Chest CT and Its Impact on Short-Term Survival.
Investigative radiology
Oct 9, 2024
OBJECTIVES: A substantial number of incidental pulmonary embolisms (iPEs) in computed tomography scans are missed by radiologists in their daily routine. This study analyzes the radiological reports of iPE cases before and after implementation of an ...
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