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Software support system for helping dermatologists in the diagnosis of the melanoma

Title : Software support system for helping dermatologists in the diagnosis of the melanoma
Abstract : --------------------------- A Research Group has developed a software support system for helping dermatologists in the diagnosis of the melanoma (a type of skin cancer). This diagnosis can use images obtained with dermatoscopic techniques and also photographs taken by the patients themselves. This system can be used as an automated way to decide the urgency to refer a patient to the dermatologist. This software is fully developed and available for demonstration. The group is open to other kind of collaboration.
Description :

Market Highlight


Clinical diagnosis on Dermatology.The software described is an expert system that can help to

the doctor for melanoma diagnosis. This system can be applied in the detection of other diseases

which are diagnosed by image analysis.

The melanoma is a type of skin cancer very aggressive and with a high incidence in many

countries like Australia, USA or European Mediterranean countries; unfortunately, each year the

number of patients is increasing. In spite of the aggressiveness of this kind of cancer, if it is

removed in early phases, the results for the patients are very good. Otherwise, if it is not

diagnosed in early phases the life expectance is reduced considerably. Therefore it is

fundamental to diagnose as soon as possible a skin lesion and to distinguish a melanoma from

benign lesions (a simple spot or a mole). Dermatologists encourage people to self-exploring and

to go to doctor if they observe a suspected skin lesion or if it is changed in a period of time.To

identify a melanoma, dermatologists use several techniques which have been developed based

on experience. All these techniques allow identifying symptoms of a malignant lesion based on

the observation of a series of characteristics. It is important to bear in mind that the diagnosis of a

melanoma through the visual interpretation of the characteristics of the lesion is a difficult task.

The Spanish Research Group has developed a system to help in the recognition of a melanoma

through the visual characteristics of an image of the skin lesion. This system can be used as an

automated way to decide the urgency to refer a patient to the dermatologist.The decision support

system for melanoma diagnosis studied has three phases: first, a preprocessing of the images

which includes the segmentation process; next, the selection of characteristics used to classify

the image; finally, the classification of the lesion.In the preprocessing phase, the system carries

out some tasks to prepare the image to be analyzed. All the digital images have impulse noise

which can be reduced applying a filter. Another task of the preprocessing phase is the

segmentation. The objective is to split objects of the scenario to get just the lesion area from the

image. For the selection of characteristics, the software is based on the ABCD rule (Asymmetry,

Border, Color, Diameter). It obtains a set of characteristics divided into three groups: one related

to the shape, other to the border and the last one to the color. The software developed use a

selection of the set of characteristics that gives the best results.The last phase of the system is

the classification of the images in two classes: benign lesions or melanoma. For the final

classification the software uses the combination of several independent classifiers. The

classification rates for the system are higher than 90%. This accurance can be incremented by

using it because this systrm can self-learn.This software is fully developed and available for

demonstration. The researchers are looking for medical services that trained and, after, validate

this software with dermatoscopic images and companies acquiring this technology for

exploitation, although the group is open to other kind of collaboration.Innovative Aspects:The

innovative aspects and advantages of the system are:• Costs reduction of melanoma campaigns.

Clinical staff can capture the photographs of the lesion and then, the system decides the urgency

to be analyzed by a specialist.• Several diagnosis proposed by artificial entities are combined to

obtain a more accurate diagnosis.• The system has been developed using web technologies so

its integration to teledermatology is direct.• System is learning continuously so as much is used,

better the results will be. The system efficiency increases with the use because it can learn by

itself as an expert system and neuronal network.

State of Development and IPR : demonstrator
Intended collaboration : joint R&D

Application or research field :

Information Communication Technology (ICT)
Medical imaging
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