AIMC Topic: Thorax

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A lightweight deep learning approach for detecting electrocardiographic lead misplacement.

Physiological measurement May 15, 2024
. Electrocardiographic (ECG) lead misplacement can result in distorted waveforms and amplitudes, significantly impacting accurate interpretation. Although lead misplacement is a relatively low-probability event, with an incidence ranging from 0.4% to...
Humans Signal Processing, Computer-Assisted Thorax Deep Learning Electrocardiography
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Influence of deep learning image reconstruction algorithm for reducing radiation dose and image noise compared to iterative reconstruction and filtered back projection for head and chest computed tomography examinations: a systematic review.

F1000Research Apr 15, 2024
BACKGROUND: The most recent advances in Computed Tomography (CT) image reconstruction technology are Deep learning image reconstruction (DLIR) algorithms. Due to drawbacks in Iterative reconstruction (IR) techniques such as negative image texture and...
Thorax Deep Learning Signal-To-Noise Ratio Humans Image Processing, Computer-Assisted Algorithms Radiography, Thoracic Head Tomography, X-Ray Computed Radiation Dosage
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HGCMorph: joint discontinuity-preserving and pose-learning via GNN and capsule networks for deformable medical images registration.

Physics in medicine and biology Mar 28, 2024
This study aims to enhance medical image registration by addressing the limitations of existing approaches that rely on spatial transformations through U-Net, ConvNets, or Transformers. The objective is to develop a novel architecture that combines C...
Thorax Image Processing, Computer-Assisted Radiology Neural Networks, Computer
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Screening and staging of chronic obstructive pulmonary disease with deep learning based on chest X-ray images and clinical parameters.

BMC pulmonary medicine Mar 26, 2024
BACKGROUND: Chronic obstructive pulmonary disease (COPD) is underdiagnosed with the current gold standard measure pulmonary function test (PFT). A more sensitive and simple option for early detection and severity evaluation of COPD could benefit prac...
Deep Learning Thorax X-Rays Retrospective Studies Pulmonary Disease, Chronic Obstructive Humans
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Hierarchical medical image report adversarial generation with hybrid discriminator.

Artificial intelligence in medicine Mar 21, 2024
BACKGROUND AND OBJECTIVES: Generating coherent reports from medical images is an important task for reducing doctors' workload. Unlike traditional image captioning tasks, the task of medical image report generation faces more challenges. Current mode...
Neural Networks, Computer Deep Learning Humans Datasets as Topic Radiography, Thoracic Image Processing, Computer-Assisted Diagnostic Imaging Thorax
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Coarse-to-fine visual representation learning for medical images via class activation maps.

Computers in biology and medicine Feb 29, 2024
The value of coarsely labeled datasets in learning transferable representations for medical images is investigated in this work. Compared to fine labels which require meticulous effort to annotate, coarse labels can be acquired at a significantly low...
Learning Thorax Neural Networks, Computer
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Artificial intelligence-based model for predicting pulmonary arterial hypertension on chest x-ray images.

BMC pulmonary medicine Feb 27, 2024
BACKGROUND: Pulmonary arterial hypertension is a serious medical condition. However, the condition is often misdiagnosed or a rather long delay occurs from symptom onset to diagnosis, associated with decreased 5-year survival. In this study, we devel...
Pulmonary Arterial Hypertension X-Rays Humans Artificial Intelligence Deep Learning Thorax
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Lung-DT: An AI-Powered Digital Twin Framework for Thoracic Health Monitoring and Diagnosis.

Sensors (Basel, Switzerland) Feb 1, 2024
The integration of artificial intelligence (AI) with Digital Twins (DTs) has emerged as a promising approach to revolutionize healthcare, particularly in terms of diagnosis and management of thoracic disorders. This study proposes a comprehensive fra...
Thorax Neural Networks, Computer Artificial Intelligence Algorithms Lung Humans
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Edge roughness quantifies impact of physician variation on training and performance of deep learning auto-segmentation models for the esophagus.

Scientific reports Jan 30, 2024
Manual segmentation of tumors and organs-at-risk (OAR) in 3D imaging for radiation-therapy planning is time-consuming and subject to variation between different observers. Artificial intelligence (AI) can assist with segmentation, but challenges exis...
Algorithms Tomography, X-Ray Computed Deep Learning Image Processing, Computer-Assisted Humans Artificial Intelligence Thorax
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Deep learning for report generation on chest X-ray images.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Dec 14, 2023
Medical imaging, specifically chest X-ray image analysis, is a crucial component of early disease detection and screening in healthcare. Deep learning techniques, such as convolutional neural networks (CNNs), have emerged as powerful tools for comput...
Deep Learning Neural Networks, Computer Humans X-Rays Diagnosis, Computer-Assisted Thorax
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