{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,31]],"date-time":"2026-07-31T09:06:49Z","timestamp":1785488809288,"version":"3.56.0"},"reference-count":36,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2025,3,7]],"date-time":"2025-03-07T00:00:00Z","timestamp":1741305600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100005322","name":"Recep Tayyip Erdogan University Development Foundation","doi-asserted-by":"publisher","award":["02024012009212"],"award-info":[{"award-number":["02024012009212"]}],"id":[{"id":"10.13039\/501100005322","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JCM"],"abstract":"<jats:p>Background and Objective: This study aims to utilize deep learning methods for the automatic segmentation of cervical lymph nodes in magnetic resonance images (MRIs), enhancing the speed and accuracy of diagnosing pathological masses in the neck and improving patient treatment processes. Materials and Methods: This study included 1346 MRI slices from 64 patients undergoing cervical lymph node dissection, biopsy, and preoperative contrast-enhanced neck MRI. A preprocessing model was used to crop and highlight lymph nodes, along with a method for automatic re-cropping. Two datasets were created from the cropped images\u2014one with augmentation and one without\u2014divided into 90% training and 10% validation sets. After preprocessing, the ResNet-50 images in the DeepLabv3+ encoder block were automatically segmented. Results: According to the results of the validation set, the mean IoU values for the DWI, T2, T1, T1+C, and ADC sequences in the dataset without augmentation created for cervical lymph node segmentation were 0.89, 0.88, 0.81, 0.85, and 0.80, respectively. In the augmented dataset, the average IoU values for all sequences were 0.91, 0.89, 0.85, 0.88, and 0.84. The DWI sequence showed the highest performance in the datasets with and without augmentation. Conclusions: Our preprocessing-based deep learning architectures successfully segmented cervical lymph nodes with high accuracy. This study is the first to explore automatic segmentation of the cervical lymph nodes using comprehensive neck MRI sequences. The proposed model can streamline the detection process, reducing the need for radiology expertise. Additionally, it offers a promising alternative to manual segmentation in radiotherapy, potentially enhancing treatment effectiveness.<\/jats:p>","DOI":"10.3390\/jcm14061802","type":"journal-article","created":{"date-parts":[[2025,3,7]],"date-time":"2025-03-07T09:38:46Z","timestamp":1741340326000},"page":"1802","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Novel Preprocessing-Based Sequence for Comparative MR Cervical Lymph Node Segmentation"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-3714-2888","authenticated-orcid":false,"given":"Elif Ayten","family":"Tarak\u00e7\u0131","sequence":"first","affiliation":[{"name":"Department of Otorhinolaryngology, Medicine Faculty, Recep Tayyip Erdo\u011fan University, Rize 53000, Turkey"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Metin","family":"\u00c7eliker","sequence":"additional","affiliation":[{"name":"Department of Otorhinolaryngology, Medicine Faculty, Recep Tayyip Erdo\u011fan University, Rize 53000, Turkey"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8184-7454","authenticated-orcid":false,"given":"Mehmet","family":"Birinci","sequence":"additional","affiliation":[{"name":"Department of Otorhinolaryngology, Medicine Faculty, Recep Tayyip Erdo\u011fan University, Rize 53000, Turkey"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tu\u011fba","family":"Yemi\u015f","sequence":"additional","affiliation":[{"name":"Department of Otorhinolaryngology, Medicine Faculty, Recep Tayyip Erdo\u011fan University, Rize 53000, Turkey"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"O\u011fuz","family":"G\u00fcl","sequence":"additional","affiliation":[{"name":"Department of Otorhinolaryngology, Ak\u00e7aabat Ha\u00e7kal\u0131 Baba State Hospital, Trabzon 61310, Turkey"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Enes Faruk","family":"O\u011fuz","sequence":"additional","affiliation":[{"name":"Department of Biomedical Device Technology, Hassa Vocational School, Hatay Mustafa Kemal University, Hatay 31000, Turkey"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3466-7260","authenticated-orcid":false,"given":"Merve","family":"Solak","sequence":"additional","affiliation":[{"name":"Department of Radiolagy, Medicine Faculty, Recep Tayyip Erdo\u011fan University, Rize 53000, Turkey"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7464-988X","authenticated-orcid":false,"given":"Esat","family":"Kaba","sequence":"additional","affiliation":[{"name":"Department of Radiolagy, Medicine Faculty, Recep Tayyip Erdo\u011fan University, Rize 53000, Turkey"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fatma Beyazal","family":"\u00c7eliker","sequence":"additional","affiliation":[{"name":"Department of Radiolagy, Medicine Faculty, Recep Tayyip Erdo\u011fan University, Rize 53000, Turkey"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zerrin","family":"\u00d6zergin Co\u015fkun","sequence":"additional","affiliation":[{"name":"Department of Otorhinolaryngology, Medicine Faculty, Recep Tayyip Erdo\u011fan University, Rize 53000, Turkey"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ahmet","family":"Alkan","sequence":"additional","affiliation":[{"name":"Department of Electrical and Electronics Engineering, Kahramanmara\u015f S\u00fct\u00e7\u00fc \u0130mam University, Kahramanmara\u015f 46000, Turkey"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"\u00d6zlem \u00c7elebi","family":"Erdivanl\u0131","sequence":"additional","affiliation":[{"name":"Department of Otorhinolaryngology, Medicine Faculty, Recep Tayyip Erdo\u011fan University, Rize 53000, Turkey"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,3,7]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"827","DOI":"10.1016\/j.mcna.2021.05.005","article-title":"Evaluation and Management of a Neck Mass","volume":"105","author":"Chorath","year":"2021","journal-title":"Med. 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