Content-Based Medical Image Retrieval System for Skin Melanoma Diagnosis Based on Optimized Pair-Wise Comparison Approach.

Medical image analysis for perfect diagnosis of disease has become a very challenging task. Due to improper diagnosis, required medical treatment may be skipped. Proper diagnosis is needed as suspected lesions could be missed by the physician's eye. Hence, this problem can be settled up by better me...

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Published in:Journal of Digital Imaging Vol. 36; no. 1; pp. 45 - 59
Main Authors: Rout, Narendra Kumar, Ahirwal, Mitul Kumar, Atulkar, Mithilesh
Format: equations & formulas pictorial research tables/charts Journal Article
Published: Springer Nature Feb2023
Online Access:View this record in EBSCOhost
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      dt: Feb2023
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      pub: Springer Nature
      place: New York, New York
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        atl: Content-Based Medical Image Retrieval System for Skin Melanoma Diagnosis Based on Optimized Pair-Wise Comparison Approach.
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          Rout, Narendra Kumar
          Ahirwal, Mitul Kumar
          Atulkar, Mithilesh
        affil: Department of Computer Application, NIT, 492010, Raipur, C.G., India
      sug:
        subj:
          Image Retrieval Systems Methods
          Diagnostic Imaging Methods
          Melanoma Diagnosis
          Skin Neoplasms Diagnosis
          Decision Making Methods
          Human
          Dermoscopy
          Algorithms
          Dermatologists
          Analytic Hierarchy Process
      ab: Medical image analysis for perfect diagnosis of disease has become a very challenging task. Due to improper diagnosis, required medical treatment may be skipped. Proper diagnosis is needed as suspected lesions could be missed by the physician's eye. Hence, this problem can be settled up by better means with the investigation of similar case studies present in the healthcare database. In this context, this paper substantiates an assistive system that would help dermatologists for accurate identification of 23 different kinds of melanoma. For this, 2300 dermoscopic images were used to train the skin-melanoma similar image search system. The proposed system uses feature extraction by assigning dynamic weights to the low-level features based on the individual characteristics of the searched images. Optimal weights are obtained by the newly proposed optimized pair-wise comparison (OPWC) approach. The uniqueness of the proposed approach is that it provides the dynamic weights to the features of the searched image instead of applying static weights. The proposed approach is supported by analytic hierarchy process (AHP) and meta-heuristic optimization algorithms such as particle swarm optimization (PSO), JAYA, genetic algorithm (GA), and gray wolf optimization (GWO). The proposed approach has been tested with images of 23 classes of melanoma and achieved significant precision and recall. Thus, this approach of skin melanoma image search can be used as an expert assistive system to help dermatologists/physicians for accurate identification of different types of melanomas.
      pubtype: Academic Journal
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        equations & formulas
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      ougenre: Article
    language: English
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