Region Adjacency Graph Approach For Acral Melanocytic Lesion Segmentation

Malignant melanoma is among the fastest increasing malignancies in many countries. Due to its propensity to metastasize and lack of effective therapies for most patients with advanced disease, early detection of melanoma is a clinical imperative. In non-Caucasian populations, melanomas are frequently located in acral volar areas and their dermoscopic appearance differs from the non-acral ones. Although lesion segmentation is a natural preliminary step towards its further analysis, so far virtually no acral skin lesion segmentation method has been proposed. Our goal was to develop an effective segmentation algorithm dedicated for acral lesions. We obtain a superpixel oversegmentation of a lesion image by performing clustering in a joint color-spatial 5d space defined by coordinates of CIELAB color space and spatial coordinates of the image. We then construct a region adjacency graph based on this superpixel representation. We obtain the ultimate segmentation result by performing a hierarchical region merging. The proposed segmentation method has been tested on 134 color dermoscopic images of different types of acral melanocytic lesions (including melanoma) from various sources. It achieved an average Dice index value of 0.85, accuracy 0.91, precision 0.89, sensitivity 0.87, and specificity 0.88. Experimental results suggest the effectiveness of the proposed method, which would help improve the accuracy of other diagnostic algorithms for acral melanoma detection. The results also suggest that the computational approach towards lesion segmentation yields more stable output than manual segmentation by dermatologists.

Malignant melanoma is among the fastest increasing malignancies in many countries. Due to its propensity to metastasize and lack of effective therapies for most patients with advanced disease, early detection of melanoma is a clinical imperative. In non-Caucasian populations, melanomas are frequently located in acral volar areas and their dermoscopic appearance differs from the non-acral ones. Although lesion segmentation is a natural preliminary step towards its further analysis, so far virtually no acral skin lesion segmentation method has been proposed. Our goal was to develop an effective segmentation algorithm dedicated for acral lesions.

Neutrosophic Set in Medical Image Analysis gives an understanding of the concepts of NS, along with knowledge on how to gather, interpret, analyze and handle medical images using NS methods. It presents the latest cutting-edge research that gives insight into neutrosophic set’s novel techniques, strategies and challenges, showing how it can be used in biomedical diagnoses systems. The neutrosophic set (NS), which is a generalization of fuzzy set, offers the prospect of overcoming the restrictions of fuzzy-based approaches to medical image analysis. Introduces the mathematical model and concepts of neutrosophic theory and methods Highlights the different techniques of neutrosophic theory, focusing on applying the neutrosophic set in image analysis to support computer- aided diagnosis (CAD) systems, including approaches from soft computing and machine learning Shows how NS techniques can be applied to medical image denoising, segmentation and classification Provides challenges and future directions in neutrosophic set based medical image analysis

In modern medicine, imaging is the most effective tool for diagnostics, treatment planning and therapy. Almost all modalities have went to directly digital acquisition techniques and processing of this image data have become an important option for health care in future. This book is written by a team of internationally recognized experts from all over the world. It provides a brief but complete overview on medical image processing and analysis highlighting recent advances that have been made in academics. Color figures are used extensively to illustrate the methods and help the reader to understand the complex topics.

This dictionary lists acronyms and abbreviations occurring with a reasonable frequency in the literature of medicine and the health care professions. Abbreviations and acronyms are given in capital letters, with no punctuation, and with concise definitions. The beginning sections also include symbols, genetic symbols, and the Greek alphabet and symbols.

As essential a text for GPs as for dermatologists, this book is an atlas-like representation of the various forms of melanocytic skin lesions associated with cutaneous melanomas and other pigmented skin tumors. It is a comprehensive and up-to-date text on the practical issues surrounding the management of individuals with these lesions. It encompasses the classical methods of morphology such as the clinical and dermoscopic examination and dermatopathology. The book also deals with the most up-to-date diagnostic approaches such as laser scanning in-vivo microscopy and automated diagnosis. The visual ‘atlas’ includes superb clinical, dermoscopic and histopathologic images.

This technique-oriented text covers the full scope of wounds and ulcerations as well as their surgical and medical management options. Features focused tables, illustrations, and step-by-step techniques for every included procedure. Special recommendations for preventing acute phases of infection are also included. (Midwest).

In this current era, neutrosophic set theory is a crucial topic to demonstrate the ambiguous information due to existence of three disjunctive components appears in it and it provides a wide range of applications in distinct fields for the researchers. Generally, neutrosophic sets is the extended version of crisp set, fuzzy set and intuitionistic fuzzy sets to focus on the uncertain, hesitant and ambiguous datas of a real life mathematical problem.