{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,10]],"date-time":"2026-09-10T19:45:55Z","timestamp":1789069555032,"version":"build-2803163510"},"reference-count":35,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2025,9,13]],"date-time":"2025-09-13T00:00:00Z","timestamp":1757721600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Science and Technology Council","award":["112-2410-H-197-002-MY2"],"award-info":[{"award-number":["112-2410-H-197-002-MY2"]}]},{"name":"National Science and Technology Council","award":["113-2314-B-182A-140"],"award-info":[{"award-number":["113-2314-B-182A-140"]}]},{"name":"National Science and Technology Council","award":["113-2221-E-131-026"],"award-info":[{"award-number":["113-2221-E-131-026"]}]},{"name":"National Science and Technology Council","award":["114-2221-E-035-032"],"award-info":[{"award-number":["114-2221-E-035-032"]}]},{"name":"National Science and Technology Council","award":["114-2221-E-131-009"],"award-info":[{"award-number":["114-2221-E-131-009"]}]},{"name":"National Science and Technology Council","award":["114-2314-B-182A-051"],"award-info":[{"award-number":["114-2314-B-182A-051"]}]},{"name":"National Science and Technology Council","award":["24H00810"],"award-info":[{"award-number":["24H00810"]}]},{"name":"Research Support of the Feng Chia University Research Program","award":["112-2410-H-197-002-MY2"],"award-info":[{"award-number":["112-2410-H-197-002-MY2"]}]},{"name":"Research Support of the Feng Chia University Research Program","award":["113-2314-B-182A-140"],"award-info":[{"award-number":["113-2314-B-182A-140"]}]},{"name":"Research Support of the Feng Chia University Research Program","award":["113-2221-E-131-026"],"award-info":[{"award-number":["113-2221-E-131-026"]}]},{"name":"Research Support of the Feng Chia University Research Program","award":["114-2221-E-035-032"],"award-info":[{"award-number":["114-2221-E-035-032"]}]},{"name":"Research Support of the Feng Chia University Research Program","award":["114-2221-E-131-009"],"award-info":[{"award-number":["114-2221-E-131-009"]}]},{"name":"Research Support of the Feng Chia University Research Program","award":["114-2314-B-182A-051"],"award-info":[{"award-number":["114-2314-B-182A-051"]}]},{"name":"Research Support of the Feng Chia University Research Program","award":["24H00810"],"award-info":[{"award-number":["24H00810"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Diagnostics"],"abstract":"<jats:p>Background\/Objectives: Pleural effusion is a common pulmonary condition that, if left untreated, may lead to respiratory distress and severe complications. Chest X-ray (CXR) imaging is routinely used by physicians to identify signs of pleural effusion. However, manually examining large volumes of CXR images on a daily basis can require substantial time and effort. To address this issue, this study proposes an automated pleural effusion detection system for CXR images. Methods: The proposed system integrates image cropping, image enhancement, and the EfficientNet-B0 deep learning model to assist in detecting pleural effusion, a task that is often challenging due to subtle symptom presentation. Image cropping was applied to extract the region from the heart to the costophrenic angle as the target area. Subsequently, image enhancement techniques were employed to emphasize pleural effusion features, thereby improving the model\u2019s learning efficiency. Finally, EfficientNet-B0 was used to train and classify pleural effusion cases based on processed images. Results: In the experimental results, the proposed image enhancement approach improved the model\u2019s recognition accuracy by approximately 4.33% compared with the non-enhanced method, confirming that enhancement effectively supports subsequent model learning. Ultimately, the proposed system achieved an accuracy of 93.27%, representing a substantial improvement of 21.30% over the 77.00% reported in previous studies, highlighting its significant advancement in pleural effusion detection. Conclusions: This system can serve as an assistive diagnostic tool for physicians, providing standardized detection results, reducing the workload associated with manual interpretation, and improving the overall efficiency of pulmonary care.<\/jats:p>","DOI":"10.3390\/diagnostics15182322","type":"journal-article","created":{"date-parts":[[2025,9,15]],"date-time":"2025-09-15T09:43:41Z","timestamp":1757929421000},"page":"2322","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Automated Computer-Assisted Diagnosis of Pleural Effusion in Chest X-Rays via Deep Learning"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-0505-3375","authenticated-orcid":false,"given":"Ya-Yun","family":"Huang","sequence":"first","affiliation":[{"name":"Program on Semiconductor Manufacturing Technology Academy of Innovative Semiconductor and Sustainable Manufacturing, National Cheng Kung University, Tainan City 701401, Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0702-5169","authenticated-orcid":false,"given":"Yu-Ching","family":"Lin","sequence":"additional","affiliation":[{"name":"Department of Medicine, College of Medicine, Chang Gung University, Taoyuan City 333423, Taiwan"},{"name":"Division of Thoracic Oncology, Department of Respiratory and Critical Care Medicine, Chang Gung Memorial Hospital, Chiayi City 613016, Taiwan"},{"name":"Department of Respiratory Care, Chang Gung University of Science and Technology, Chiayi County 61363, Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sung-Hsin","family":"Tsai","sequence":"additional","affiliation":[{"name":"Department of Medical Education, Chang Gung Memorial Hospital Linkou, Taoyuan City 333423, Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-7109-6492","authenticated-orcid":false,"given":"Tsun-Kuang","family":"Chi","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, Ming Chi University of Technology, New Taipei City 243303, Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-5964-6084","authenticated-orcid":false,"given":"Tsung-Yi","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Electronic Engineering, Feng Chia University, Taichung City 40724, Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shih-Wei","family":"Chung","sequence":"additional","affiliation":[{"name":"Department of Electronic Engineering, Feng Chia University, Taichung City 40724, Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0110-5491","authenticated-orcid":false,"given":"Kuo-Chen","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Information Management, Chung Yuan Christian University, Taoyuan City 320317, Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1134-5859","authenticated-orcid":false,"given":"Wei-Chen","family":"Tu","sequence":"additional","affiliation":[{"name":"Program on Semiconductor Manufacturing Technology Academy of Innovative Semiconductor and Sustainable Manufacturing, National Cheng Kung University, Tainan City 701401, Taiwan"},{"name":"Department of Electronic Engineering, National Cheng Kung University, Tainan City 701401, Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8848-6644","authenticated-orcid":false,"given":"Patricia Angela","family":"R. Abu","sequence":"additional","affiliation":[{"name":"Ateneo Laboratory for Intelligent Visual Environments, Department of Information Systems and Computer Science, Ateneo de Manila University, Quezon City 1108, Philippines"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chih-Cheng","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Automatic Control Engineering, Feng Chia University, Taichung City 40724, Taiwan"},{"name":"Department of Aeronautical Engineering, Chaoyang University of Technology, Taichung City 41349, Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,9,13]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"7001504","DOI":"10.1109\/LSENS.2022.3167121","article-title":"Automated Detection of Pulmonary Diseases From Lung Sound Signals Using Fixed-Boundary-Based Empirical Wavelet Transform","volume":"6","author":"Tripathy","year":"2022","journal-title":"IEEE Sens. 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