AIMC Topic: Tomography, X-Ray Computed
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Automated orofacial virtual patient creation: A proof of concept.
Journal of dentistry
Oct 2, 2024
OBJECTIVES: To (1) construct a virtual patient (VP) using facial scan, intraoral scan, and low-dose computed tomography scab based on an Artificial intelligence (AI)-approach, (2) quantitatively compare it with AI-refined and semi-automatic registrat...
Accurate prediction of disease-risk factors from volumetric medical scans by a deep vision model pre-trained with 2D scans.
Nature biomedical engineering
Oct 1, 2024
The application of machine learning to tasks involving volumetric biomedical imaging is constrained by the limited availability of annotated datasets of three-dimensional (3D) scans for model training. Here we report a deep-learning model pre-trained...
Role of artificial intelligence in treatment planning and outcome prediction of jaw corrective surgeries by using 3-D imaging: a systematic review.
Oral surgery, oral medicine, oral pathology and oral radiology
Oct 1, 2024
OBJECTIVE: Artificial intelligence (AI) has been increasingly utilized in diagnosis of skeletal deformities, while its role in treatment planning and outcome prediction of jaw corrective surgeries with 3-dimensional (3D) imaging remains underexplored...
Deep Learning-Based Synthetic Computed Tomography for Low-Field Brain Magnetic Resonance-Guided Radiation Therapy.
International journal of radiation oncology, biology, physics
Oct 1, 2024
PURPOSE: Magnetic resonance (MR)-guided radiation therapy enables online adaptation to address intra- and interfractional changes. To address the need of high-fidelity synthetic computed tomography (synCT) required for dose calculation, we developed ...
Artificial Intelligence in Temporal Bone Imaging: A Systematic Review.
The Laryngoscope
Oct 1, 2024
OBJECTIVE: The human temporal bone comprises more than 30 identifiable anatomical components. With the demand for precise image interpretation in this complex region, the utilization of artificial intelligence (AI) applications is steadily increasing...
Multi-instance learning for identifying high-risk subregions associated with synchronous distant metastasis in clear cell renal cell carcinoma.
Medical physics
Oct 1, 2024
BACKGROUND: Clear cell renal cell carcinoma (ccRCC) is one of the most common histological subtypes of renal tumors.
Preoperative markers for identifying CT ≤2 cm solid nodules of lung adenocarcinoma based on image deep learning.
Thoracic cancer
Oct 1, 2024
BACKGROUND: The solid pattern is a highly malignant subtype of lung adenocarcinoma. In the current era of transitioning from lobectomy to sublobar resection for the surgical treatment of small lung cancers, preoperative identification of this subtype...
Machine learning models based on CT radiomics features for distinguishing benign and malignant vertebral compression fractures in patients with malignant tumors.
Acta radiologica (Stockholm, Sweden : 1987)
Oct 1, 2024
BACKGROUND: Radiomics has become an important tool for distinguishing benign and malignant vertebral compression fractures (VCFs). It is more clinically significant to concentrate on patients who have malignant tumors and differentiate between benign...
Reconstructing and analyzing the invariances of low-dose CT image denoising networks.
Medical physics
Sep 30, 2024
BACKGROUND: Deep learning-based methods led to significant advancements in many areas of medical imaging, most of which are concerned with the reduction of artifacts caused by motion, scatter, or noise. However, with most neural networks being black ...
Personalized prediction of immunotherapy response in lung cancer patients using advanced radiomics and deep learning.
Cancer imaging : the official publication of the International Cancer Imaging Society
Sep 30, 2024
BACKGROUND: Lung cancer (LC) is a leading cause of cancer-related mortality, and immunotherapy (IO) has shown promise in treating advanced-stage LC. However, identifying patients likely to benefit from IO and monitoring treatment response remains cha...
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