Melanoma is one of the fatal forms of skin cancer, and has become more common, especially among white-skinned people exposed to the sun. Early detection of melanoma is essential to increase survival rates, since its detection in an early stage can be helpful and curable. Working out the dermoscopic clinical features of melanoma is an important step for dermatologists, who need an accurate way of reaching the correct clinical diagnosis, and to ensure the right area gets the right treatment. In this paper, we present a comprehensive approach including image enhancement, segmentation of lesions and melanoma detection, to allow for early detection of malignant melanoma disease. As an image enhancement, the Gabor filter, image sharpening, Sobel filter and image inpainting methods are integrated to delete unwanted objects (noise). The lesion border segmentation is performed by combining the Particle Swarm Optimization and the Markov Random Field approaches. To be able to determine the lesions types, the K-means is applied on the segmented lesion, to separate it into homogeneous clusters, where important features are extracted, then an Artificial Neural Network is trained by representative features to classify the given lesion as melanoma or not. The whole experimental results obtained on a public database PH2 and compared with existing methods in the literature have shown that our proposed approach is accurate, robust, and efficient in the segmentation of the lesion boundary, as well as its classification.

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Abstract

Dear colleagues, Asalamu Alykum

Welcome to the group of dermatologists in Libya, which hosts specialists and dermatologists and those who are involved in the training program for specialization, through which subjects related to the specialization are posted in the form of different formulas and scenarios, for example clinical patient photos or theoretical topics for discussion or the introduction of

topics of medical literature for enrichment Discussion, sharing and

exchange of experiences among fellows in the CME course

In view of the privacy of the group in terms of which medical cases are reviewed with pictures of patients, it is necessary to join those with the

real name of the doctor and do not accept the aliases and only admission to

doctors and their names the truth and we hope from the colleagues

appreciate this point. In order to protect us from individual ownership, it is

not permissible to present pictures of patients' cases except by the doctor

concerned. It should be noted that there is no room in this group for

advertising propaganda and promotional all types and keep them as a

scientific group and even the names of drugs must be mentioned scientific

names. I also hope that all members will participate actively and enrich the

discussion so that the benefit will prevail. May Allah guide us all to what

is good and God is behind the intention.

ABSTRACT

Libya is one of the largest countries in the olive oil production leading to

generate massive amounts of olive-waste cakes during the manufacture process

every year. Therefore, this experimental study aims to investigate the potential of

olive-waste cake as a low-cost natural source for preparation activated carbon

(AC). The solid olive oil mill residue was carbonized at 200 0C and chemically

activated using two methods including Model I (25% Zncl2) and Model II (25%

Zncl2 + 25% H2SO2) . To investigate the efficiency of prepared AC,decolourization of methylene blue founded in an aqueous solution was conducted. The effectiveness of this process was studied via key parameters

effects such as contact time, pH, and AC dose. The achieved results showed that

the decolourization using Model II was more than of Model I. The optimum

values of pH, contact time, and AC dose were 5, 120 min, and 2.5 g/L

respectively. At these conditions the maximum methylene blue removal was

75%. The results indicate that olive-waste cake has a potential in future water

treatment applications due to its high adsorption capacity.