About Our Project

”Dermatologist Assistant” is an mobile application and computer-aided diagnosis (CAD) tool with an objective of speeding up the detection of lesion areas in skin. Our proposed system is available for all users types that are concerned with dermatology (Skin Cancer) issues. All that appears as options through a friendly GUI, after capturing any lesion are and request classification for it.
We will implement a non-existing system with a high accuracy, speed differentiation and detection of various type of cancers . Our cancer detector goes through three essential stages. Firstly, uploading image for skin. Secondly, testing the image after applying different algorithms. Finally, classifying whether the disease is (melomna, basic cell cariona, nevus ).
Starting with pre-processing which will be performed on the uploaded image from mobile phone that will be made on the mobile . Then, segmentation by applying threshold which will be made on the server . After that is feature extraction, mainly extracting 11 features which are (Mean , Standard Deviation ,Skewness ,Kurtosis ,Smoothness, Homogenity , Contrast , Energy,Entropy,surf,sift). Final step is classification using different algorithms to train and test the dataset.
The system stores medical records to save patients medical history And the system have a doctor sign up that is made by the admin and the patient can register easily . It also has the ability of learning from miss-classified tests to enhance the future accuracy of the system.

Proposal

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SRS (Software Recruitment Specification)

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Research Paper

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SDD (Software Design Document)

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Diagrams

Class Diagram

Context Diagram

Block Diagram


About Diseases

Basal Cell Carcinoma


Researches Summaries

Four Class Classification of Skin Lesions with Task Decomposition Strategy

Deep Residual Neural Networks for Automated Basal Cell Carcinoma Detection

Basal Cell Carcinoma Detection in Full Field OCT Images Using Convolutional Neural

Automatic detection of basal cell carcinoma using vascular-extracted features from dermoscopy

Automated Detection and Segmentation of Vascular Structures of Skin Lesions Seen in Dermoscopy, with an application to Basal Cell Carcinoma Classification


About Our Team

Hagar Maher

012 266 186 57

hagar1403073@miuegypt.edu.eg

2014/03073

Ehab Mustafa

015 505 601 48

ehab1509994@miuegypt.edu.eg

2015/09994

Alaa Muhamed

010 951 858 79

alaa1508223@miuegypt.edu.eg

2015/08223