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Related Concept Videos

Imaging Studies for Cardiovascular System IV: CMRI01:21

Imaging Studies for Cardiovascular System IV: CMRI

Cardiovascular magnetic resonance imaging, or CMRI, is a non-invasive diagnostic test that employs a magnetic field and radiofrequency waves to create precise images of the heart and arteries. It provides comprehensive information about cardiac anatomy, function, perfusion, and tissue characterization without ionizing radiation.IndicationsCMRI diagnoses various heart conditions, including tissue damage from heart attacks, ischemic heart disease, myocarditis, aortic issues (tears, aneurysms,...
Imaging Studies for Cardiovascular System V: CT01:28

Imaging Studies for Cardiovascular System V: CT

Cardiac computed tomography (CT) scanning is an advanced cardiac imaging technique that utilizes CT technology, with or without intravenous (IV) contrast, to produce accurate cross-sectional virtual slices of specific areas of the heart, coronary circulation, and major blood vessels such as the aorta, pulmonary veins, and arteries. The computer processes these slices to generate three-dimensional images. Multidetector CT (MDCT) is a rapid form of CT scanning that captures multiple slices...
Imaging Studies for Cardiovascular System VI: Calcium -Scoring CT01:25

Imaging Studies for Cardiovascular System VI: Calcium -Scoring CT

Calcium-Scoring CT ScanA calcium-scoring CT scan, also known as coronary artery calcium (CAC) scan, detects calcium deposits in the coronary arteries. This test assesses the risk of coronary artery disease (CAD), which can lead to cardiovascular events such as angina, heart failure, and sudden cardiac arrest.A calcium-scoring CT scan is generally recommended for individuals at intermediate risk of CAD without symptoms. It includes:Men aged 40-75 and women aged 50-75: Especially those with a...

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Related Experiment Video

Updated: Jun 18, 2026

Automated Segmentation of Cortical Grey Matter from T1-Weighted MRI Images
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[Ischemic stroke infarct segmentation model based on depthwise separable convolution for multimodal magnetic

Yidong Jin1, Mengfei Wang1, Jingjing Chen2

  • 1School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, P. R. China.

Sheng Wu Yi Xue Gong Cheng Xue Za Zhi = Journal of Biomedical Engineering = Shengwu Yixue Gongchengxue Zazhi
|June 27, 2024
PubMed
Summary

This study introduces a new deep learning model for segmenting ischemic stroke lesions in MRI scans. The novel network improves accuracy in identifying stroke areas, aiding clinical diagnosis and treatment planning.

Keywords:
Atrous convolutionDepthwise separable convolutionInfarct segmentationMultimodalStroke

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Area of Science:

  • Medical imaging analysis
  • Artificial intelligence in healthcare
  • Neurology

Context:

  • Magnetic resonance imaging (MRI) is vital for diagnosing ischemic stroke.
  • Accurate infarct segmentation is critical for treatment and prognosis.
  • Existing methods struggle with multiscale stroke lesion segmentation.

Purpose:

  • To develop a novel encoder-decoder network for improved ischemic stroke lesion segmentation.
  • To enhance the extraction of multiscale features and segmentation accuracy.

Summary:

  • A new network utilizes depthwise separable convolutions and modified Atrous spatial pyramid pooling (MASPP).
  • An attention gate (AG) structure is integrated into skip connections to refine multiscale target segmentation.
  • The proposed method was evaluated on the ISLES2022 dataset, achieving superior performance metrics.

Impact:

  • The algorithm significantly improves infarct lesion segmentation accuracy.
  • This advancement offers reliable support for clinical diagnosis and treatment of ischemic stroke.
  • Enhanced segmentation facilitates better patient prognosis evaluation.