Important: Use custom search function to get better results from our thousands of pages

Use " " for compulsory search eg:"electronics seminar" , use -" " for filter something eg: "electronics seminar" -"/tag/" (used for exclude results from tag pages)
Ask More Info Of  A Seminar Ask More Info Of A Project Post Reply  Follow us on Twitter
21-02-2012, 11:03 AM
Post: #1
Automatic Segmentation of Skin Cancer Images using Adaptive Color Clustering

Automatic Segmentation of Skin Cancer Images using Adaptive Color Clustering


.pdf  Auto Seg- colour clusturing.pdf (Size: 700.87 KB / Downloads: 22)

Introduction
Skin cancer is one of the most common types of cancer and it can affect people at any age. It is a malignant tumor that develops changes in the skin texture and color, but it can be cured in more than 90% of cases, if the skin tumor is detected and treated in the early stages. There are two types of skin cancer, namely malignant melanoma and non-melanoma (basal cell and squamous cell carcinoma) [1]. Melanoma is more dangerous and can be fatal if untreated and a number of commercially available systems are designed for the analysis of pigmented skin lesions. Two representative systems are the SolarScan [2] and the microDERM dermoscopy unit [3]. It is useful to note that these systems are designed primarily to accurately capture skin images and not for automated detection of skin cancer images which is the aim of the image segmentation technique detailed in this paper.


Image Segmentation Algorithm
The main components of the developed image segmentation algorithm are illustrated in Fig. 1. The key component of the algorithm is the Adaptive Spatial K-Means clustering algorithm that is included in the development of a split and merge color-texture segmentation framework.


Experiments and Results
To evaluate the performance of the proposed algorithm, we use six representative skin lesion images depicted in Figs. 2 and 3. It can be noticed that the boundaries of some lesions are not well defined since parts of melanoma have characteristics of healthy skin tissue. To be able to determine the accuracy of the developed algorithm we constructed the ground truth by tracing manually the outline of the melanoma (see Fig. 4).


Conclusions
The aim of this paper is to present a novel algorithm for segmentation of skin cancer images by evaluating adaptively the color and texture information. The main novelty of this approach is the development of an adaptive spatially coherent color-clustering scheme (A-SKM) that is included in the implementation of a color texture segmentation algorithm. The resulting color-texture algorithm proved to produce accurate segmentation of low-resolution skin cancer images that are defined by large color and texture non-uniformities. This research is on-going and we plan to investigate ways of improving accuracy and to evaluate the performance of our algorithm when applied to large collections of skin cancer images.
Rating Automatic Segmentation of Skin Cancer Images using Adaptive Color Clustering Options
Share Automatic Segmentation of Skin Cancer Images using Adaptive Color Clustering To Your Friends :- Seminar Topics Bookmark
Post Reply 

Marked Categories : project report download skin cancer segmentation, segmentation of skin cancer images ppt, skin cancer detection, color segmentation, cell determination using image segmentation, skin cancer detection algorithms, skin tumor segmentation techniques, post your skin cancer pictures, automated skin cancer detection news, skin texture segmentation, k means algorithm cancer color,

[-]
Quick Reply
Message
Type your reply to this message here.


Image Verification
Image Verification
(case insensitive)
Please enter the text within the image on the left in to the text box below. This process is used to prevent automated posts.

Possibly Related Threads...
Thread: Author Replies: Views: Last Post
  automatic discovery system seminar report project maker 0 32 23-09-2014 11:15 AM
Last Post: project maker
  Implementation of Adaptive Viterbi Decoder Seminar Report seminar code 0 66 09-09-2014 10:06 AM
Last Post: seminar code
  Document Clustering using Rough K-means Algorithm Seminar Report seminar code 0 62 01-09-2014 03:37 PM
Last Post: seminar code
  ADAPTIVE BLIND NOISE SUPPRESSION SEMINAR TOPIC data seminar 0 92 27-08-2014 04:38 PM
Last Post: data seminar
  ADAPTIVE BLIND NOISE SUPPRESSION SEMINAR REPORT project maker 0 52 27-08-2014 03:49 PM
Last Post: project maker
  ADAPTIVE MAC IN MANET SEMINAR TOPIC data seminar 0 48 23-08-2014 12:11 PM
Last Post: data seminar
  Energy Efficient Clustering Approaches for Wireless Sensor Networks: A Comprehensive seminar code 0 80 04-08-2014 11:12 AM
Last Post: seminar code
  Sensitive Skin : Seminar Report and PPT study tips 0 65 07-06-2014 12:39 PM
Last Post: study tips
  Web Clustering Engines : Seminar Report and PPT seminar post 0 103 05-06-2014 02:16 PM
Last Post: seminar post
  Smart Skin for Machine Handling : Seminar Report and PPT seminar projects maker 0 101 05-06-2014 10:43 AM
Last Post: seminar projects maker
This Page May Contain What is Automatic Segmentation of Skin Cancer Images using Adaptive Color Clustering And Latest Information/News About Automatic Segmentation of Skin Cancer Images using Adaptive Color Clustering,If Not ...Use Search to get more info about Automatic Segmentation of Skin Cancer Images using Adaptive Color Clustering Or Ask Here

Options: