AIMC Journal:
Medical physics

Showing 271 to 280 of 732 articles

Deep learning in ultrasound elastography imaging: A review.

Medical physics Jul 30, 2022
It is known that changes in the mechanical properties of tissues are associated with the onset and progression of certain diseases. Ultrasound elastography is a technique to characterize tissue stiffness using ultrasound imaging either by measuring t...
Neural Networks, Computer Algorithms Deep Learning Ultrasonography Elasticity Imaging Techniques
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Combining natural and artificial intelligence for robust automatic anatomy segmentation: Application in neck and thorax auto-contouring.

Medical physics Jul 27, 2022
BACKGROUND: Automatic segmentation of 3D objects in computed tomography (CT) is challenging. Current methods, based mainly on artificial intelligence (AI) and end-to-end deep learning (DL) networks, are weak in garnering high-level anatomic informati...
Humans Artificial Intelligence Cone-Beam Computed Tomography
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Multiscale unsupervised domain adaptation for automatic pancreas segmentation in CT volumes using adversarial learning.

Medical physics Jul 27, 2022
PURPOSE: Computer-aided automatic pancreas segmentation is essential for early diagnosis and treatment of pancreatic diseases. However, the annotation of pancreas images requires professional doctors and considerable expenditure. Due to imaging diffe...
Tomography, X-Ray Computed Deep Learning Image Processing, Computer-Assisted Pancreas
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Deep learning-based synthetization of real-time in-treatment 4D images using surface motion and pretreatment images: A proof-of-concept study.

Medical physics Jul 22, 2022
PURPOSE: To develop a deep learning model that maps body surface motion to internal anatomy deformation, which is potentially applicable to dose-free real-time 4D virtual image-guided radiotherapy based on skin surface data.
Humans Deep Learning Proof of Concept Study
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Deep learning for brain metastasis detection and segmentation in longitudinal MRI data.

Medical physics Jul 22, 2022
PURPOSE: Brain metastases (BM) occur frequently in patients with metastatic cancer. Early and accurate detection of BM is essential for treatment planning and prognosis in radiation therapy. Due to their tiny sizes and relatively low contrast, small ...
Humans Brain Neoplasms Deep Learning Magnetic Resonance Imaging
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Intracranial vessel wall segmentation with deep learning using a novel tiered loss function incorporating class inclusion.

Medical physics Jul 21, 2022
PURPOSE: To develop an automated vessel wall segmentation method on T1-weighted intracranial vessel wall magnetic resonance images, with a focus on modeling the inclusion relation between the inner and outer boundaries of the vessel wall.
Humans Deep Learning Vascular Diseases
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Deep learning methods for enhancing cone-beam CT image quality toward adaptive radiation therapy: A systematic review.

Medical physics Jul 18, 2022
The use of deep learning (DL) to improve cone-beam CT (CBCT) image quality has gained popularity as computational resources and algorithmic sophistication have advanced in tandem. CBCT imaging has the potential to facilitate online adaptive radiation...
Humans Deep Learning Cone-Beam Computed Tomography Image Processing, Computer-Assisted Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage Phantoms, Imaging Radiometry
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A deep learning-based automatic system for intracranial aneurysms diagnosis on three-dimensional digital subtraction angiographic images.

Medical physics Jul 15, 2022
BACKGROUND: Intracranial aneurysms (IAs) are a life-threatening disease. Their rupture can lead to hemorrhagic stroke. Most studies applying deep learning for the detection of aneurysms are based on angiographic images. However, critical diagnostic i...
Humans Deep Learning Angiography, Digital Subtraction Intracranial Aneurysm
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A novel end-to-end deep learning solution for coronary artery segmentation from CCTA.

Medical physics Jul 11, 2022
PURPOSE: Coronary computed tomographic angiography (CCTA) plays a vital role in the diagnosis of cardiovascular diseases, among which automatic coronary artery segmentation (CAS) serves as one of the most challenging tasks. To computationally assist ...
Deep Learning Coronary Vessels
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Single-shot T mapping via multi-echo-train multiple overlapping-echo detachment planar imaging and multitask deep learning.

Medical physics Jul 10, 2022
BACKGROUND: Quantitative magnetic resonance imaging provides robust biomarkers in clinics. Nevertheless, the lengthy scan time reduces imaging throughput and increases the susceptibility of imaging results to motion. In this context, a single-shot T ...
Humans Deep Learning
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