Harnessing Deep Learning for Accurate Pathological Assessment of Brain Tumor Cell Types.
Primary diffuse central nervous system large B-cell lymphoma (CNS-pDLBCL) and high-grade glioma (HGG) often present similarly, clinically and on imaging, making differentiation challenging. This similarity can complicate pathologists' diagnostic efforts, yet accurately distinguishing between these c...
| Published in: | Journal of Imaging Informatics in Medicine Vol. 38; no. 2; pp. 1098 - 1112 |
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| Main Authors: | , , , , , , , |
| Format: | equations & formulas pictorial research tables/charts Journal Article |
| Published: |
Springer Nature
Apr2025
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=184081716&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 184081716 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 29482925 NR3A jtl: Journal of Imaging Informatics in Medicine issn: 29482925 maglogo: N pubinfo: dt: Apr2025 vid: 38 iid: 2 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 184081716 184081716 184081716 10.1007/s10278-024-01107-9 184081716 ppf: 1098 ppct: 14 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Harnessing Deep Learning for Accurate Pathological Assessment of Brain Tumor Cell Types. aug: au: Tian, Chongxuan Xi, Yue Ma, Yuting Chen, Cai Wu, Cong Ru, Kun Li, Wei Zhao, Miaoqing affil: https://ror.org/0207yh398 School of Control Science and Engineering, Shandong University, 250061, Jinan, Shandong, China sug: subj: Deep Learning Brain Neoplasms Classification Brain Neoplasms Pathology Image Processing, Computer Assisted Image Interpretation, Computer Assisted Funding Source Support Vector Machine Convolutional Neural Networks Glioma Classification Lymphoma, B-Cell Classification Lymphoma, B-Cell Diagnosis Glioma Diagnosis Human Software Machine Learning Data Management Algorithms Contrast Media Diagnostic Use Probability Sensitivity and Specificity Validity False Positive Results ab: Primary diffuse central nervous system large B-cell lymphoma (CNS-pDLBCL) and high-grade glioma (HGG) often present similarly, clinically and on imaging, making differentiation challenging. This similarity can complicate pathologists' diagnostic efforts, yet accurately distinguishing between these conditions is crucial for guiding treatment decisions. This study leverages a deep learning model to classify brain tumor pathology images, addressing the common issue of limited medical imaging data. Instead of training a convolutional neural network (CNN) from scratch, we employ a pre-trained network for extracting deep features, which are then used by a support vector machine (SVM) for classification. Our evaluation shows that the Resnet50 (TL + SVM) model achieves a 97.4% accuracy, based on tenfold cross-validation on the test set. These results highlight the synergy between deep learning and traditional diagnostics, potentially setting a new standard for accuracy and efficiency in the pathological diagnosis of brain tumors. pubtype: Academic Journal doctype: equations & formulas pictorial research tables/charts Journal Article ougenre: Unknown language: English refInfo: holdings: @attributes: islocal: N |
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