Abnormal localization of immature precursors (ALIP) detection for early prediction of acute myelocytic leukemia (AML) relapse.
Acute myelocytic leukemia (AML) is a relapsing and deadly disease. Thus, it is important to early predict leukemia relapse. Recent studies have demonstrated strong correlations of relapse with abnormal localization of immature precursors (ALIP). However, there is no related research on automated det...
| Publicado en: | Medical & Biological Engineering & Computing Vol. 52; no. 2; pp. 121 - 130 |
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| Autores principales: | , , , |
| Formato: | research Journal Article |
| Publicado: |
Springer Nature
Feb2014
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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=104010958&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 104010958 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01400118 PO0 jtl: Medical & Biological Engineering & Computing issn: 01400118 maglogo: N pubinfo: dt: Feb2014 vid: 52 iid: 2 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 104010958 NLM24363095 2012455928 10.1007/s11517-013-1122-x NLM24363095 104010958 ppf: 121 ppct: 9 formats: fmt: @attributes: type: P tig: atl: Abnormal localization of immature precursors (ALIP) detection for early prediction of acute myelocytic leukemia (AML) relapse. aug: au: Huang, Hai-Qing Fang, Xiang-Zhong Shi, Jun Hu, Jie affil: School of Electronic, Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, People's Republic of China. sug: subj: Bone Marrow Pathology Leukemia, Myeloid, Acute Diagnosis Neoplasm Recurrence, Local Diagnosis Adolescence Adult Aged Bone Marrow Female Image Processing, Computer Assisted Male Middle Age Prognosis Young Adult Adolescent: 13-18 years Adult: 19-44 years Aged: 65+ years Middle Aged: 45-64 years Female Male ab: Acute myelocytic leukemia (AML) is a relapsing and deadly disease. Thus, it is important to early predict leukemia relapse. Recent studies have demonstrated strong correlations of relapse with abnormal localization of immature precursors (ALIP). However, there is no related research on automated detection of ALIP so far. To this end, we have proposed an ALIP detection method to investigate the relevance with AML relapse. Kernelized fuzzy C-means clustering is applied first to separate the foreground (with cells) and background (without cells). Image repairing is then used to wipe out noises to mark region of interest. Then, image partition is introduced to separate the overlapping cells. After that, a set of features are extracted for the classification. Thereafter, support vector machine is applied to classify precursors. At last, filtering operations are applied to obtain the binary-precursor detection results. Thirty-seven patients with AML are examined. The results show that ALIP is efficiently detected in a high sensitivity and positive predictive value by our proposed method. The investigation also demonstrates the strong correlations of AML relapse with ALIP. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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