A blueprint for the synthesis and characterization of thiolated graphene

Graphene derivatization to either engineer its physical and chemical properties or overcome the problem of the facile synthesis of nanographenes is a subject of significant attention in the nanomaterials research community. In this paper, we propose a facile and scalable method for the synthesis of thiolated graphene via a two step liquid phase treatment of graphene oxide GO . Employing the core level methods, the introduction of up to 5.1 at. of thiols is indicated with the simultaneous rise of the C O ratio to 16.8. The crumpling of the graphene layer upon thiolation without its perforation is pointed out by microscopic and Raman studies. The conductance of thiolated graphene is revealed to be driven by the Mott hopping mechanism with the sheet resistance values of 2.15 k amp; 937; sq and dependable on the environment. The preliminary results on the chemiresistive effect of these films upon exposure to ethanol vapors in the mix with dry and humid air are shown. Finally, the work function value and valence band structure of thiolated graphene are analyzed. Taken together, the developed method and findings of the morphology and physics of the thiolated graphene guide the further application of this derivative in energy storage, sensing devices, and smart material

Detection of Circles as Structural Elements in Dermatoscopic Images of Skin Neoplasms in the Diagnosis of Melanoma

A method for recognizing “circles”, significant structural elements of skin neoplasms, has been proposed. An RDS-2 dermatoscope has been used for imaging. Special software has been developed to implement the proposed method for circle recognition. The results of experimental detection of circles are presented. The developed method can be used in diagnostic systems for detecting skin melanoma, a dangerous form of cancer. © 2021, Springer Science+Business Media, LLC, part of Springer Nature

A Model for Recognizing Structureless Hyperpigmented Areas in Dermato-Oncology

A model for recognizing structureless hyperpigmented areas in images of skin neoplasms has been developed. Recognition of hyperpigmented areas is important for the diagnosis of skin melanoma, a rapidly progressing skin cancer. A digital dermatoscope RDS-2 has been used to obtain images serving as the initial data for the model. Software for recognizing hyperpigmentation areas in images of skin neoplasms has been developed on the basis of the proposed model. Tests have shown the recognition accuracy to be 82%. The proposed model can be recommended for use in decision-making support systems for the diagnosis of melanoma. © 2022, Springer Science+Business Media, LLC, part of Springer Nature

Model of a Decision-Making System for the Diagnosis of Melanoma Using Artificial Intelligence

Interdisciplinary approaches to creating high-tech computer systems for the diagnosis of melanoma using artificial intelligence are presented. A model is proposed for the architecture of an interactive expert system. This includes a set of features for a contemporary medical algorithm (the Kittler algorithm) along with a knowledge base and a diagnosis evaluation score for the case under study. © 2021, Springer Science+Business Media, LLC, part of Springer Nature

Color recognition of dermatoscopic images of skin neoplasms

The problem of determining the colors of dermatoscopic images of skin neoplasms using computer technologies is considered. Based on the proposed model, a program for recognizing the colors of the studied areas of neoplasm has been developed. The adequacy of this model was tested experimentally. This work is designed to increase the reliability of the diagnosis of skin neoplasms. © 2021 Institute of Physics Publishing. All rights reserved

A Model for Recognition of Dermatoscopic Points in Images of Skin Neoplasms

The challenges of using computer diagnostics to seek structural elements of melanocytic neoplasms, including cutaneous melanomas at early stages of their development, are discussed. The characteristic features of the structural elements — dermatoscopic points — are also considered. A computer vision technique for recognizing these characteristic features is presented. The developed interdisciplinary approach can be used in the diagnosis of oncological diseases of the skin as a means of supporting decision making for the primary prevention of malignant neoplasms. © 2021, Springer Science+Business Media, LLC, part of Springer Nature

A Model for Detecting Structural Elements – Lines – in Digital Images in Oncodermatology

The problem of early diagnosis of one of the most dangerous malignant neoplasms of the skin, melanoma, is considered. A model for detecting structural elements (lines) in digital images of skin neoplasms in oncodermatology has been developed. The model is based on adaptive binarization of the initial digital dermatoscopy image of skin les neoplasms ions and subsequent operations of dilation, erosion, skeletonization, and filtration of false line fragments. Test dermatoscopy images of skin neoplasms were visually divided into four groups to conduct the experiment. Optimal parameters of image processing of four groups for the model of detecting structural elements – lines – have been experimentally established. The experimentally determined accuracy of line detection was 95%. This research is the result of interdisciplinary cooperation of dermatologists of the Central Medical Academy of the Administrative Department of the President of the Russian Federation, the Medical Institute of the Russian Peoples’ Friendship University and experts in the field of information and measurement systems of the Engineering and Physical Institute of Biomedicine of the National Research Nuclear University “MEPhI”. The proposed model can be used in the development of computer systems to support medical decision-making in the diagnosis of skin melanoma – a dangerous malignant neoplasm. © 2021, Springer Science+Business Media, LLC, part of Springer Nature

Model for Assessing the Asymmetry of a Pigmented Neoplasm

Abstract The paper presents the results of the development of a method for recognizing skin neoplasms based on a model for assessing the asymmetry of the shape of the pigment area of the pathological growth of the epidermis and (or) dermis. Images of pigmented skin neoplasms obtained using a dermatoscope were considered as initial data. To analyze the images, a model was used to calculate the shape asymmetry coefficients obtained relative to the main axes of inertia of the neoplasm, which makes it possible to obtain values independent of the angle of rotation of the images