Delineation of the ischemic stroke lesion based on watershed and relative fuzzy connectedness in brain MRI.
Precise segmentation of stroke lesions from brain magnetic resonance (MR) images poses a challenging task in automated diagnosis. In this paper, we proposed a new method called watershed-based lesion segmentation algorithm (WLSA), which is a novel intensity-based segmentation technique used to delin...
| Publicado en: | Medical & Biological Engineering & Computing Vol. 56; no. 5; pp. 795 - 808 |
|---|---|
| Autores principales: | , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
May2018
|
| 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=129156213&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 129156213 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01400118 PO0 jtl: Medical & Biological Engineering & Computing issn: 01400118 maglogo: N pubinfo: dt: May2018 vid: 56 iid: 5 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 129156213 129156213 NLM28948480 10.1007/s11517-017-1726-7 NLM28948480 129156213 ppf: 795 ppct: 13 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Delineation of the ischemic stroke lesion based on watershed and relative fuzzy connectedness in brain MRI. aug: au: Subudhi, Asit Jena, Subhranshu Sabut, Sukanta affil: Department of Electronics and Communication Engineering, ITER, SOA University, Bhubaneswar, Odisha, India sug: subj: Stroke Diagnosis Logic Cerebral Ischemia Diagnosis Magnetic Resonance Imaging Algorithms Brain Pathology Middle Age ROC Curve Reproducibility of Results Female Time Factors Image Interpretation, Computer Assisted Male Middle Aged: 45-64 years Female Male ab: Precise segmentation of stroke lesions from brain magnetic resonance (MR) images poses a challenging task in automated diagnosis. In this paper, we proposed a new method called watershed-based lesion segmentation algorithm (WLSA), which is a novel intensity-based segmentation technique used to delineate infarct lesion in diffusion-weighted imaging (DWI) MR images of the brain. The algorithm was tested on a series of 142 real-time images collected from different stroke patients reported at IMS and SUM Hospital. One MRI slice having largest area of infract lesion is selected from each patient from multiple slices. The main objective is to combine the strength of guided filter and watershed transform through relative fuzzy connectedness (RFC) to detect lesion boundaries appropriately. The extracted informative statistical and geometrical features are used to classify the types of stroke lesions according to the Oxfordshire Community Stroke Project (OCSP) classification. The experimental results demonstrated the effectiveness of the proposed process with high accuracy in delineating lesions. A classification with a dice similarity index (DSI) of 96% with computational time of 0.06 s in random forest (RF) and an accuracy of 85% with computational time of 0.84 s has been obtained by multilayer perceptron (MLP) neural network classifier in tenfold cross-validation process. Better detection accuracy is achieved in RF classifier in classifying stroke lesions. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
|---|