Melanoma - skin cancer reviewed

Skin Image ProcessingMay 31, 2006 6:30 pm
The MoleExpert software is a product is based on experiences of many years with the automated analysis of pigmented skin lesions. Important requirement with this software project was the usefulness of the software with most different photograph systems.

Qualitatively high-quality, evenly and well illuminated top illumination-microscopic pictures of the lesions is the most important condition for the operability of this software.

MoleExpert micro software
 

MoleExpert micro was developed for the support of the diagnostic identification. The system spends no diagnosis for this reason, but supplies as results of measurement data to asymmetry, for the delimitation of the lesion, to the color and to the size. These parameters of the ABCD rule are recognized for some years as important dermatoskopic parameters. According to a special algorithm adapted on the image analysis the four ABCD values are combined into a total core, which can take values between zero to unify. With lesions with high Score, it acts with higher probability around a Melanoma, than with lesions with low Score.
Download demo version from here: MoleExpert micro

Melanoma Articles, Skin Image ProcessingMay 15, 2006 1:01 pm

If quality skin model is constructed, then recognizing skin cancer symptoms can be easier as there are many factors showing about threat of skin cancer. Of course this can’t give 100% results, as there are many shortcomings connected with skin lesion variety and interpretation errors. But some guides may help.

There are 3 main factors that can indicate risk of skin cancer. Recognizing skin cancer symptoms can be based on them. They are:

  • Melanin presence in papillary dermis;
  • Thickness of papillary dermis;
  • Blood behavior around the lesion and inside it.

Firs of all Melanin presence in dermis. This is the main factor in recognizing skin cancer symptoms. If there is melanin spreaded in papillary dermis or even dermis, this is a big probability of being skin cancer symptoms, but not always. There are several sub factors in this issue like melanin spreading figure, depth, and melanin density within this shape. If there are more irregularities in spreading area there are more risks.

Recognizing skin cancer symptoms

 

Other factor in recognizing skin cancer symptoms is papillary layer thickness. In not going in to deep too much there can be said, that thinner this layer, the bigger risk.

Recognizing skin cancer symptoms

And last figure, which can be noticed even with eye, is the blood shape. Usually around risky lesions there is more intense blood feed. The area around lesion is more reddish, while inside the blood is diminished. It is explained, that there is bigger demand of blood to grow and divide caner cells.

  Recognizing skin cancer symptoms

But again recognizing skin cancer symptoms is not only inspecting these values, while there can be benign lesions with symptoms indicating skin cancer. These indicators can only help in overall diagnosis.

 
 
Skin Image ProcessingMay 4, 2006 8:09 pm

SkinSeg is simple tool used for skin lesion segmentation. This little program was developed by Intelligent Systems laboratory students: L. Xu, M. Jackowski, A. Goshtasby, C. Yu, D. Roseman, S. Bines, A. Dhawan, A. Huntley. Their method is working similar as in my earlier experiment with matlab pigmented lesion boundary tracing algorithm. First image is converted to intensity image and then the lesion edges are detected.

malignant melanoma tracing boundary 

ant test results:

Malignant melanoma tracing 

More informative description you can find here 

Program can be downloaded from here: http://www.cs.wright.edu/people/faculty/agoshtas/skinseg.zip 

This version of the Skin Cancer Segmentation program (skinseg) runs on the Windows 95/NT platforms. Make sure all files reside in the same directory after extraction. No setup program is required to install skinseg on your machine. To run, execute the program skinseg.exe.

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