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      <dc:title>Automatic Analysis of Ultrasound Images to Estimate Subcutaneous and Visceral Fat and Muscle Tissue in Patients with Suspected Malnutrition.</dc:title>
      <dc:creator>Cuesta-Vargas, Antonio</dc:creator>
      <dc:creator>Arjona-Caballero, José María</dc:creator>
      <dc:creator>Olveira-Fuster, Gabriel María</dc:creator>
      <dc:creator>De Luis Román, Daniel</dc:creator>
      <dc:creator>Bellido-Guerrero, Diego</dc:creator>
      <dc:creator>García-Almeida, José Manuel</dc:creator>
      <dc:subject>Diagnóstico por imagen</dc:subject>
      <dc:subject>Malnutrición</dc:subject>
      <dc:subject>Cuerpo humano - Composición</dc:subject>
      <dc:subject>Músculos</dc:subject>
      <dc:subject>Visión por ordenador</dc:subject>
      <dc:subject>Inteligencia artificial</dc:subject>
      <dc:description>Background: Malnutrition is a prevalent condition associated with adverse&#xd;
health outcomes, requiring the accurate assessment of muscle composition and fat distribution.&#xd;
Methods: This study presents a novel method for the automatic analysis of&#xd;
ultrasound images to estimate subcutaneous and visceral fat, as well as muscle, in patients&#xd;
with suspected malnutrition. The proposed system utilizes computer vision techniques to&#xd;
segment regions of interest (ROIs), calculate relevant variables, and store data for clinical&#xd;
evaluation. Unlike traditional segmentation methods that rely solely on thresholding or&#xd;
pre-defined masks, our method employs an iterative hierarchical approach to refine contour&#xd;
detection and improve localization accuracy. A dataset of abdominal and leg ultrasound&#xd;
images, captured in both longitudinal and transversal planes, was analyzed. &#xd;
Results: Results showed higher precision for longitudinal scans compared to transversal scans,&#xd;
particularly for length-related variables, with the Y-axis Vastus intermediate achieving a&#xd;
precision of 92.87%. However, area-based measurements demonstrated lower precision&#xd;
due to differences between manual adjustments by experts and automatic geometric approximations.&#xd;
Conclusions: These findings highlight the system’s potential for clinical use&#xd;
while emphasizing the need for further algorithmic refinements to improve precision in&#xd;
area calculations.</dc:description>
      <dc:date>2025-04-24T10:22:33Z</dc:date>
      <dc:date>2025-04-24T10:22:33Z</dc:date>
      <dc:date>2025-04-13</dc:date>
      <dc:type>journal article</dc:type>
      <dc:identifier>Cuesta-Vargas, A.; Arjona-Caballero, J.M.; Olveira, G.; de Luis Román, D.; Bellido-Guerrero, D.; García-Almeida, J.M. Automatic Analysis of Ultrasound Images to Estimate Subcutaneous and Visceral Fat and Muscle Tissue in Patients with Suspected Malnutrition. Diagnostics 2025, 15, 988. https://doi.org/10.3390/diagnostics15080988</dc:identifier>
      <dc:identifier>https://hdl.handle.net/10630/38475</dc:identifier>
      <dc:identifier>10.3390/diagnostics15080988</dc:identifier>
      <dc:language>eng</dc:language>
      <dc:rights>http://creativecommons.org/licenses/by/4.0/</dc:rights>
      <dc:rights>open access</dc:rights>
      <dc:rights>Attribution 4.0 Internacional</dc:rights>
      <dc:publisher>MDPI</dc:publisher>
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