AIMC Topic: Thorax
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Deep learning-based age estimation from clinical Computed Tomography image data of the thorax and abdomen in the adult population.
PloS one
Nov 7, 2023
Aging is an important risk factor for disease, leading to morphological change that can be assessed on Computed Tomography (CT) scans. We propose a deep learning model for automated age estimation based on CT- scans of the thorax and abdomen generate...
How intra-source imbalanced datasets impact the performance of deep learning for COVID-19 diagnosis using chest X-ray images.
Scientific reports
Nov 3, 2023
Over the past decade, the use of deep learning has been widely increasing in the medical image diagnosis field. Deep learning-based methods' (DLMs) performance strongly relies on training data. Therefore, researchers often focus on collecting as much...
SUnet: A multi-organ segmentation network based on multiple attention.
Computers in biology and medicine
Oct 18, 2023
Organ segmentation in abdominal or thoracic computed tomography (CT) images plays a crucial role in medical diagnosis as it enables doctors to locate and evaluate organ abnormalities quickly, thereby guiding surgical planning, and aiding treatment de...
Deep Learning for Detection and Localization of B-Lines in Lung Ultrasound.
IEEE journal of biomedical and health informatics
Sep 6, 2023
Lung ultrasound (LUS) is an important imaging modality used by emergency physicians to assess pulmonary congestion at the patient bedside. B-line artifacts in LUS videos are key findings associated with pulmonary congestion. Not only can the interpre...
Raw data consistent deep learning-based field of view extension for dual-source dual-energy CT.
Medical physics
Aug 31, 2023
BACKGROUND: Due to technical constraints, dual-source dual-energy CT scans may lack spectral information in the periphery of the patient.
New trend in artificial intelligence-based assistive technology for thoracic imaging.
La Radiologia medica
Aug 28, 2023
Although there is no solid agreement for artificial intelligence (AI), it refers to a computer system with intelligence similar to that of humans. Deep learning appeared in 2006, and more than 10 years have passed since the third AI boom was triggere...
Fully automatic deep learning-based lung parenchyma segmentation and boundary correction in thoracic CT scans.
International journal of computer assisted radiology and surgery
Aug 18, 2023
PURPOSE: The proposed work aims to develop an algorithm to precisely segment the lung parenchyma in thoracic CT scans. To achieve this goal, the proposed technique utilized a combination of deep learning and traditional image processing algorithms. T...
Phase Unwrapping of Color Doppler Echocardiography Using Deep Learning.
IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Aug 2, 2023
Color Doppler echocardiography is a widely used noninvasive imaging modality that provides real-time information about intracardiac blood flow. In an apical long-axis view of the left ventricle, color Doppler is subject to phase wrapping, or aliasing...
Frequency constraint-based adversarial attack on deep neural networks for medical image classification.
Computers in biology and medicine
Jul 25, 2023
The security of AI systems has gained significant attention in recent years, particularly in the medical diagnosis field. To develop a secure medical image classification system based on deep neural networks, it is crucial to design effective adversa...
Efficient Feature-Selection-Based Stacking Model for Stress Detection Based on Chest Electrodermal Activity.
Sensors (Basel, Switzerland)
Jul 25, 2023
Contemporary advancements in wearable equipment have generated interest in continuously observing stress utilizing various physiological indicators. Early stress detection can improve healthcare by lessening the negative effects of chronic stress. Ma...
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