title: Detection of constituent layers of histological oral sub-mucous fibrosis: images using the hybrid segmentation algorithm.
abstract: This paper concentrates on the segmentation of histological images of oral sub-mucous fibrosis (OSF) into its constituent layers. In this regard hybrid segmentation algorithm shows very interesting results. The segmentation results depict the superiority of hybrid segmentation algorithm (HSA) in comparison to region growing algorithm (RGA). In clinical sense, the presented method provides an automatic means for segmenting histological layers (reference class map provided by the expert). The method shows potential in mimicking clinical acumen to act as a support system to oncologist.
authors.affiliation: Department of Electrical Engineering, Indian Institute of Technology, West Bengal, Kharagpur 721 302, India.
authors.forename: Tathagata
authors.initials: T
authors.lastname: Ray
authors.forename: D Shivashanker
authors.initials: DS
authors.lastname: Reddy
authors.forename: Anirban
authors.initials: A
authors.lastname: Mukherjee
authors.forename: Jyotirmoy
authors.initials: J
authors.lastname: Chatterjee
authors.forename: Ranjan R
authors.initials: RR
authors.lastname: Paul
authors.forename: Pranab K
authors.initials: PK
authors.lastname: Dutta
mesh_terms: D000465:Algorithms; D005355:Fibrosis; D006801:Humans; D007089:Image Enhancement; D007090:Image Interpretation, Computer-Assisted; D008279:Magnetic Resonance Imaging; D009061:Mouth Mucosa / Q000473:pathology*; D009062:Mouth Neoplasms / Q000473:pathology*; D011230:Precancerous Conditions / Q000473:pathology*; D015203:Reproducibility of Results