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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.
Alphaherpesviruses are a fascinating group of DNA viruses that includes important human pathogens such as herpes simplex virus type 1 (HSV-1), HSV-2, and varicella-zoster virus (VZV): the causative agents of cold sores, genital ulcerous disease, and chickenpox/shingles, respectively. A key attribute of these viruses is their ability to establish lifelong latent infection in the peripheral nervous system of the host. Such persistence requires subversion of the host's immune system and intrinsic antiviral defense mechanisms. Understanding the mechanisms of the immune evasion and what triggers viral reactivation is a major challenge for today's researchers. This has prompted enormous research efforts into understanding the molecular and cellular biology of these viruses. This up-to-date and comprehensive volume aims to distill the most important research in this area providing a timely overview of the field. Topics covered include: transcriptional regulation, DNA replication, translational control, virus entry and capsid assembly, the role of microRNAs in infection and oncolytic vectors for cancer therapy. In addition there is coverage of virus-host interactions, including apoptosis, subversion of host protein quality control and DNA damage response pathways, autophagy, establishment and reactivation from latency, interferon responses, immunity and vaccine development. Essential reading for everyone working with alphaherpesviruses and of interest to all virologists working on latent infections.
This paper proposes novel skin lesion detection based on neutrosophic clustering and adaptive region growing algorithms applied to dermoscopic images, called NCARG. First, the dermoscopic images are mapped into a neutrosophic set domain using the shearlet transform results for the images.
In this paper one generalizes the intuitionistic fuzzy set (IFS), paraconsistent set, and intuitionistic set to the neutrosophic set (NS). Many examples are presented. Distinctions between NS and IFS are underlined.
In this work, we present definition of interval valued neutrosophic parameterized (IVNP-)soft set and its operations. Then we define parameter reduction method for IVNP-soft set.We also give an example which shows that they can be successfully applied to problem that contains indeterminacy.
As a generalization of fuzzy sets and intuitionistic fuzzy sets, neutrosophic sets have been developed to represent uncertain, imprecise, incomplete, and inconsistent information existing in the real world. And interval neutrosophic sets (INSs) have been proposed exactly to address issues with a set of numbers in the real unit interval, not just a specific number.However, there are fewer reliable operations for INSs, as well as the INS aggregation operators and decisionmakingmethod. For this purpose, the operations for INSs are defined and a comparison approach is put forward based on the related research of interval valued intuitionistic fuzzy sets (IVIFSs) in this paper. On the basis of the operations and comparison approach, two interval neutrosophic number aggregation operators are developed. Then, amethod formulticriteria decisionmaking problems is explored applying the aggregation operators. In addition, an example is provided to illustrate the application of the proposed method.