Melanoma - skin cancer reviewed :: May

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 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

Recognizing skin cancer symptoms using model based imaging

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.

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.

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 – segmentation of melanoma

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.

Skin Image ProcessingMay 1, 2006 10:19 am

DullRazor – digital skin hair shaver

DullRasor uses image processing techniques to analyze and segmentates skin areas with dark hair. This program removes dark hairs form images, and makes skin lesion images clean to further processing.

Skin image with lesion and hairs Skin image with lesion and without hairs

Many skin images contain various numbers of hairs. Other skin segmentation programs may mislead because of hairs – especially dark ones. One solution can be shaving skin before taking pictures of it. But shaving of skin adds more time to processing and this is uncomfortable and in some cases unesthetical. Hence, a software approach for dark thick hair removal from skin images is needed.

There is only one program window:

DullRazor

DullRazor performs the following steps:

It identifies the dark hair locations by a generalized grayscale morphological closing operation,
It verifies the shape of the hair pixels as thin and long structure, and replace the verified pixels by a bilinear interpolation;
It smoothes the replaced hair pixels with an adaptive median filter.

The algorithm has been implemented in C on a SunOS 4.x workstation. (The program can be run on Sun Solaris workstations as well.) It has been tested on real nevi images with satisfactory results.

Download the Unix version of DullRazor (dullrazor.zip, 87KB).
Download the Windows version of DullRazor (dullrazor_wins.zip, 327KB.

My personal test on one of images:

Skin lesion with hairs