Paper Title

SKIN CANCER DIAGNOSIS-LESION SEGMENTATION-REVIEW STUDY

Article Identifiers

Registration ID: IJNRD_219317

Published ID: IJNRD2404778

DOI: Click Here to Get

Authors

GEETHANJALI B N

Keywords

1. Skin lesion segmentation 2. Dermoscopic image analysis 3. Melanoma detection 4. ISIC 2017 dataset 5. Deep learning 6. Convolutional neural networks (CNNs) 7. Image processing 8. Segmentation algorithms 9. Performance evaluation 10. Similarity metrics

Abstract

Skin lesion segmentation plays a crucial role in computer-aided diagnosis of melanoma-most invasive Skin cancer with highest risk of Death. This paper presents a comprehensive review and comparative analysis of state-of-the-art skin lesion segmentation methods using the ISIC 2017 dataset. The dataset, consisting of dermoscopic images of skin lesions, poses unique challenges due to variations in lesion size, shape, and texture. Various deep learning and traditional image processing techniques are explored and evaluated for their effectiveness in segmenting skin lesions accurately for the early detection of Skin cancer which helps in early diagnosis. Performance metrics such as Dice coefficient, Jaccard index, Accuracy, Sensitivity, Specificity are employed to quantify the similarity between the segmented regions and ground truth annotations. The results provide valuable insights into the effectiveness of different segmentation methods and their suitability for use in clinical practice. The results highlight the strengths and limitations of different approaches, providing insights for future research in this domain.

How To Cite

"SKIN CANCER DIAGNOSIS-LESION SEGMENTATION-REVIEW STUDY", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.9, Issue 4, page no.h734-h737, April-2024, Available :https://ijnrd.org/papers/IJNRD2404778.pdf

Issue

Volume 9 Issue 4, April-2024

Pages : h734-h737

Other Publication Details

Paper Reg. ID: IJNRD_219317

Published Paper Id: IJNRD2404778

Downloads: 000121250

Research Area: Computer Science & Technology 

Country: HASSAN, KARNATAKA, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2404778.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2404778

About Publisher

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

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Call For Paper

Call For Paper - Volume 10 | Issue 8 | August 2025

IJNRD is Scholarly open access journals, Peer-reviewed, and Refereed Journals, High Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool), Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI) with Open-Access Publications.

INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (IJNRD) aims to explore advances in research pertaining to applied, theoretical and experimental Technological studies. The goal is to promote scientific information interchange between researchers, developers, engineers, students, and practitioners working in and around the world. IJNRD will provide an opportunity for practitioners and educators of engineering field to exchange research evidence, models of best practice and innovative ideas.

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Paper Submission Open For: August 2025

Current Issue: Volume 10 | Issue 8

Last Date for Paper Submission: Till 31-Aug-2025

Notification of Review Result: Within 1-2 Days after Submitting paper.

Publication of Paper: Within 01-02 Days after Submititng documents.

Frequency: Monthly (12 issue Annually).

Journal Type: International Peer-reviewed, Refereed, and Open Access Journal.

Subject Category: Research Area