Detection of mitotic HEp-2 cell images: role of feature representation and classification framework under class skew.
We propose and analyze a framework to detect and identify the mitotic type staining patterns among different non-mitotic (interphase) patterns on HEp-2 cell substrate specimen images. This is considered as a principal task in computer-aided diagnosis (CAD) of the autoimmune disorders. Due to the rar...
| Publicado en: | Medical & Biological Engineering & Computing Vol. 60; no. 8; pp. 2405 - 2422 |
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| Autores principales: | , , |
| Formato: | equations & formulas pictorial research tables/charts Journal Article |
| Publicado: |
Springer Nature
Aug2022
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=158037392&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 158037392 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01400118 PO0 jtl: Medical & Biological Engineering & Computing issn: 01400118 maglogo: N pubinfo: dt: Aug2022 vid: 60 iid: 8 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 158037392 158037392 NLM35773609 158037392 10.1007/s11517-022-02613-0 NLM35773609 158037392 ppf: 2405 ppct: 17 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Detection of mitotic HEp-2 cell images: role of feature representation and classification framework under class skew. aug: au: Gupta, Krati Bhavsar, Arnav Sao, Anil K. affil: School of Computing & Electrical Engineering, Indian Institute of Technology Mandi, Mandi, India sug: subj: Diagnosis, Computer Assisted Methods Human ab: We propose and analyze a framework to detect and identify the mitotic type staining patterns among different non-mitotic (interphase) patterns on HEp-2 cell substrate specimen images. This is considered as a principal task in computer-aided diagnosis (CAD) of the autoimmune disorders. Due to the rare appearance of mitotic patterns in whole slide/specimen images, the sample skew between mitotic and non-mitotic patterns is an important consideration.We suggest to apply some effective samples skew balancing strategies for the task of classification between mitotic v/s interphase patterns. Another aspect of this study is to consider the morphology and texture-based differences between both the classes that can be incorporated through effective morphology and texture-based descriptors, including the Gabor and LM (Leung-Malik) filter banks and also through some contemporary filter banks derived from convolutional neural networks (CNN).The proposed framework is evaluated on a public dataset and we demonstrate good performance (0.99 or 1 Matthews correlation coefficient (MCC) in many cases), across various experiments. The study also presents a comparison between hand-engineered and CNN-based feature representation, along with the comparisons with state-of-the-art approaches. Hence, the framework proves to be a good solution for the mentioned skewed classification problem. pubtype: Academic Journal doctype: equations & formulas pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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