Detection of Melanoma Skin Cancer using Segmentation and Classification Algorithms

نویسندگان

  • I. S. Akila
  • Jeffrey Glaister
  • David A. Clausi
  • Pedram Ghamisi
  • Micael S. Couceiro
  • Fernando M. L. Martins
  • Jon Atli Benediktsson
  • J. Glaister
  • R. Amelard
  • A. Wong
  • C. Scharfenberger
  • K. Fergani
  • J. S. Zelek
  • P. G. Cavalcanti
چکیده

Melanoma is the most dangerous skin cancer. It should be diagnosed early because of its aggressiveness. To diagnose melanoma earlier, skin lesion should be segmented accurately. To reduce the cost for specialists to screen every patient, there is a need of automated melanoma prescreening system to diagnose melanoma using images acquired in digital cameras. In this frame work, an automated melanoma prescreening system is proposed to diagnose melanoma skin cancer using Modified TDLS algorithm and SVM classifier. Representative texture distributions are obtained from texture vectors. The segmentation accuracy is improved by modification in TDLS algorithm. TD metric is calculated with lesion texture distributions only. The entire system is tested using MATLAB software.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Non-melanoma skin cancer diagnosis with a convolutional neural network

Background: The most common types of non-melanoma skin cancer are basal cell carcinoma (BCC), and squamous cell carcinoma (SCC). AKIEC -Actinic keratoses (Solar keratoses) and intraepithelial carcinoma (Bowen’s disease)- are common non-invasive precursors of SCC, which may progress to invasive SCC, if left untreated. Due to the importance of early detection in cancer treatment, this study aimed...

متن کامل

Melanoma detection with a deep learning model

Background: Skin cancer is one of the most common forms of cancer in the world and melanoma is the deadliest type of skin cancer. Both melanoma and melanocytic nevi begin in melanocytes (cells that produce melanin). However, melanocytic nevi are benign whereas melanoma is malignant. This work proposes a deep learning model for classification of these two lesions.    Methods: In this analytic s...

متن کامل

Detection of Melanoma Skin Cancer by Elastic Scattering Spectra: A Proposed Classification Method

Introduction: There is a strong need for developing clinical technologies and instruments for prompt tissue assessment in a variety of oncological applications as smart methods. Elastic scattering spectroscopy (ESS) is a real-time, noninvasive, point-measurement, optical diagnostic technique for malignancy detection through changes at cellular and subcellular levels, especially important in ear...

متن کامل

A New Algorithm for Skin Lesion Border Detection in Dermoscopy Images

Background: With advances in medical imaging systems, digital dermoscopy has become one of the major imaging modalities in the analysis of skin lesions. Thus, automated segmentation or border detection has a great impact on the subsequent steps of skin cancer computer-aided diagnosis using demoscopy images. Since dermoscopy images suffer from artifacts such as shading and hair, there is a need ...

متن کامل

A Novel Method for Skin Lesion Segmentation

Skin cancer has been the most usual and illustrates 50% of all new cancers detected each year. If they detected at an early stage, treatment can become simple and economically. Accurate skin lesion segmentation is important in automated early skin cancer detection and diagnosis systems. The aim of this study is to provide an effective approach to detect the skin lesion border on a purposed imag...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2015