Download or read book Skin Cancer Segmentation Using Neural Network written by Ginni Arora and published by LAP Lambert Academic Publishing. This book was released on 2012-07 with total page 72 pages. Available in PDF, EPUB and Kindle. Book excerpt: Skin cancer is the most common form of cancer in United States. If detected at an early stage simple and economic treatments can cure skin cancers. Accurate skin lesion segmentation is critical in automated skin cancer early detection and diagnosis. This book proposes methods like explicit pixel based, median filter, difference filter, conservative smoothing and Kohonen neural network for automated segmentation which can replace traditional biopsy and dermoscopes. Further it can give direction to dermatologists in detecting ABCD's of skin cancer. Also may help research scholars, practitioners and students to understand more about image processing methods and role of neural network in segmentation.

Download or read book Metaheuristics and Optimization in Computer and Electrical Engineering written by Navid Razmjooy and published by Springer Nature. This book was released on 2020-11-16 with total page 311 pages. Available in PDF, EPUB and Kindle. Book excerpt: The use of artificial intelligence, especially in the field of optimization is increasing day by day. The purpose of this book is to explore the possibility of using different kinds of optimization algorithms to advance and enhance the tools used for computer and electrical engineering purposes.

Download or read book Skin Cancer Detection Using Generative Adversarial Network and an Ensemble of Deep Convolutional Neural Networks written by Aakriti Adhikari and published by . This book was released on 2019 with total page 116 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the past few years, Deep learning has been widely used in medical imaging for classification and segmentation and has been successful in providing better diagnostic accuracy. The state-of- the-art deep learning algorithms are built using neural networks arranged in layers where the first layer extracts basic information of images like edges, colors etc so that the output of one layer is fed as input to the next consecutive layers. Thus, increasing the complexity of learning with increase of layers. In comparison with the traditional machine learning algorithms, deep learning has many advantages and is an automatic process. However, it requires large scale annotated data for better performance and is thus constrained by limited size of available public datasets. To overcome data constraints, this thesis proposes a more efficient and novel scheme comprising techniques that use an ensemble of convolution neural networks (CNN) with generative adversarial network (GAN) based augmentation to improve the diagnostic accuracy. Also, the implementation of the proposed technique on skin lesion dataset of limited size to classify melanoma is presented. In this work, images are augmented to increase the dataset size using two different augmentation techniques: traditional augmentation and GAN based augmentation. GAN based augmentation is based on neural networks, where, two neural networks compete against each other to produce visually realistic synthetic images. For the classification, CNN and an ensemble of CNNs are trained on the final enlarged training dataset comprising original images and synthetic images. Here, the ensemble of CNN techniques combines five trained CNNs into a single meta-classifier. One hundred and ninety-three skin lesion test images were used to validate our proposed methods. The first method proposed in this research incorporated traditional to enlarge the training dataset and trained a CNN classifier to classify skin cancer into malignant or benign. The performance of the model on the test dataset was observed with 79.29% of accuracy, 77% sensitivity and 81.38% specificity. The second proposed method incorporated both traditional augmentation and GAN based augmentation to enlarge the training dataset and a CNN classifier was trained in a similar way as compared to the first method. This method was validated with 81.32% accuracy, 80.26% sensitivity and 82.78% specificity. The final proposed method utilized both of these augmentation techniques to enlarge the training dataset and an ensemble of five CNN classifiers was trained for the classification. It performed better with the performance accuracy of 84.30% , sensitivity of 84.32% and specificity of 84.21% . Further, it prevented trapping into local maxima, causing performance to increase. The scheme with the proposed methods can be a better choice while dealing with the limited training dataset.

Download or read book Dermoscopy Image Analysis written by M. Emre Celebi and published by CRC Press. This book was released on 2015-10-16 with total page 458 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dermoscopy is a noninvasive skin imaging technique that uses optical magnification and either liquid immersion or cross-polarized lighting to make subsurface structures more easily visible when compared to conventional clinical images. It allows for the identification of dozens of morphological features that are particularly important in identifyin

Download or read book Artificial Neural Networks and Machine Learning ICANN 2014 written by Stefan Wermter and published by Springer. This book was released on 2014-08-18 with total page 874 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book constitutes the proceedings of the 24th International Conference on Artificial Neural Networks, ICANN 2014, held in Hamburg, Germany, in September 2014. The 107 papers included in the proceedings were carefully reviewed and selected from 173 submissions. The focus of the papers is on following topics: recurrent networks; competitive learning and self-organisation; clustering and classification; trees and graphs; human-machine interaction; deep networks; theory; reinforcement learning and action; vision; supervised learning; dynamical models and time series; neuroscience; and applications.

Download or read book Sensors and Image Processing written by Shabana Urooj and published by Springer. This book was released on 2017-10-03 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume comprises the select proceedings of the annual convention of the Computer Society of India. Divided into 10 topical volumes, the proceedings present papers on state-of-the-art research, surveys, and succinct reviews. The volumes cover diverse topics ranging from communications networks to big data analytics, and from system architecture to cyber security. This volume focuses on Sensors and Image Processing. The contents of this book will be useful to researchers and students alike.

Download or read book OR 2 0 Context Aware Operating Theaters Computer Assisted Robotic Endoscopy Clinical Image Based Procedures and Skin Image Analysis written by Danail Stoyanov and published by Springer. This book was released on 2018-10-01 with total page 338 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed joint proceedings of the First International Workshop on OR 2.0 Context-Aware Operating Theaters, OR 2.0 2018, 5th International Workshop on Computer Assisted Robotic Endoscopy, CARE 2018, 7th International Workshop on Clinical Image-Based Procedures, CLIP 2018, and the First International Workshop on Skin Image Analysis, ISIC 2018, held in conjunction with the 21st International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2018, in Granada, Spain, in September 2018. The 11 full papers presented at OR 2.0 2018, the 5 full papers presented at CARE 2018, the 8 full papers presented at CLIP 2018, and the 10 full papers presented at ISIC 2018 were carefully reviewed and selected. The OR 2.0 papers cover a wide range of topics such as machine vision and perception, robotics, surgical simulation and modeling, multi-modal data fusion and visualization, image analysis, advanced imaging, advanced display technologies, human-computer interfaces, sensors. The CARE papers cover topics to advance the field of computer-assisted and robotic endoscopy. The CLIP papers cover topics to fill gaps between basic science and clinical applications. The ISIC papers cover topics to facilitate knowledge dissemination in the field of skin image analysis, as well as to host a melanoma detection challenge, raising awareness and interest for these socially valuable tasks.

Download or read book Multimedia Signals and Systems written by Mrinal Kr. Mandal and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 383 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multimedia Signals and Systems is primarily a technical introductory level multimedia textbook, including problems, examples, and MATLAB® codes. It will be a stepping-stone for readers who want to research in audio processing, image and video processing, and data compression. This book will also be useful to readers who are carrying out research and development in systems areas such as television engineering and storage media. Anyone who seeks to learn the core multimedia signal processing techniques and systems will need Multimedia Signals and Systems. There are many chapters that are generic in nature and provide key concepts of multimedia systems to technical as well as non-technical persons. There are also several chapters that provide a mathematical/ analytical framework for basic multimedia signal processing. The readers are expected to have some prior knowledge about discrete signals and systems, such as Fourier transform and digital filters. However, a brief review of these theories is provided. Additional material for this book, including several MATLAB® codes along with a few test data samples; e.g., audio, image and video may be downloaded from http://extras.springer.com.

Download or read book 2021 XLVII Latin American Computing Conference CLEI written by IEEE Staff and published by . This book was released on 2021-10-25 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: CLEI Conference brings together researchers, professionals, teachers and students in a forum to discuss topics related to the areas of Computer Science, Computer Engineering, Information Systems and other courses in computing, as well as the direct impact of ICT (Information and Communication Technologies) in society as a whole It aims at exchanging ideas, experiences and research results in the areas of interest of the community, through conferences, workshops, tutorials and panels

Download or read book Input Space Augmentation for Skin Lesion Segmentation in Dermoscopic Images written by Abhishek Kumar and published by . This book was released on 2020 with total page 66 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cancer is the second leading cause of death globally, and of all the cancers, skin cancer is the most prevalent. Early diagnosis of skin cancer is a crucial step for maximizing patient survival rates and treatment outcomes. Skin conditions are often diagnosed by dermatologists based on the visual properties of the affected regions, motivating the utility of automated algorithms to assist dermatologists and offer viable, low-cost, and quick results to assist dermatological diagnoses. Over the last decade, machine learning, and more recently, deep learning-based diagnoses of skin lesions have started approaching human performance levels. This thesis studies approaches to improve the segmentation of skin lesions in dermoscopic images, which is often the first and the most important task in the diagnosis of dermatological conditions. In particular, we present two methods to improve deep learning-based segmentation of skin lesions by augmenting the input space of convolutional neural network models. In the first contribution, we address the problem of the paucity of annotated data by learning to synthesize artificial skin lesion images conditioned on input segmentation masks. We then use these synthetic image mask pairs to augment our original segmentation training datasets. In our second contribution, we leverage certain color channels and skin imaging- and illumination-based knowledge in a deep learning framework to augment the input space of the segmentation models. We evaluate the two contributions on five dermoscopic image datasets: the ISIC Skin Lesion Segmentation Challenge 2016, 2017, and 2018 datasets, the DermoFit Image Library, and the PH2 Database, and observe performance improvements across all datasets.

Download or read book Handbook of Dermoscopy written by Josep Malvehy and published by CRC Press. This book was released on 2006-01-17 with total page 106 pages. Available in PDF, EPUB and Kindle. Book excerpt: The rise in popularity of dermoscopy has meant that more and more practitioners need a ready reference to consult in a clinical setting where larger atlases are less practical. The Handbook of Dermoscopy features a wealth of photographs, checklists, and algorithms to assist in spot diagnoses. Coverage includes melanocytic lesions, seborrheic kerato

Download or read book Concepts and Real Time Applications of Deep Learning written by Smriti Srivastava and published by Springer Nature. This book was released on 2021-09-23 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides readers with a comprehensive and recent exposition in deep learning and its multidisciplinary applications, with a concentration on advances of deep learning architectures. The book discusses various artificial intelligence (AI) techniques based on deep learning architecture with applications in natural language processing, semantic knowledge, forecasting and many more. The authors shed light on various applications that can benefit from the use of deep learning in pattern recognition, person re-identification in surveillance videos, action recognition in videos, image and video captioning. The book also highlights how deep learning concepts can be interwoven with more modern concepts to yield applications in multidisciplinary fields. Presents a comprehensive look at deep learning and its multidisciplinary applications, concentrating on advances of deep learning architectures; Includes a survey of deep learning problems and solutions, identifying the main open issues, innovations and latest technologies; Shows industrial deep learning in practice with examples/cases, efforts, challenges, and strategic approaches.

Download or read book Computer Vision Techniques for the Diagnosis of Skin Cancer written by Jacob Scharcanski and published by Springer Science & Business Media. This book was released on 2013-09-30 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt: The goal of this volume is to summarize the state-of-the-art in the utilization of computer vision techniques in the diagnosis of skin cancer. Malignant melanoma is one of the most rapidly increasing cancers in the world. Early diagnosis is particularly important since melanoma can be cured with a simple excision if detected early. In recent years, dermoscopy has proved valuable in visualizing the morphological structures in pigmented lesions. However, it has also been shown that dermoscopy is difficult to learn and subjective. Newer technologies such as infrared imaging, multispectral imaging, and confocal microscopy, have recently come to the forefront in providing greater diagnostic accuracy. These imaging technologies presented in this book can serve as an adjunct to physicians and provide automated skin cancer screening. Although computerized techniques cannot as yet provide a definitive diagnosis, they can be used to improve biopsy decision-making as well as early melanoma detection, especially for patients with multiple atypical nevi.

Download or read book Machine Learning for Healthcare Applications written by Sachi Nandan Mohanty and published by John Wiley & Sons. This book was released on 2021-04-13 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: When considering the idea of using machine learning in healthcare, it is a Herculean task to present the entire gamut of information in the field of intelligent systems. It is, therefore the objective of this book to keep the presentation narrow and intensive. This approach is distinct from others in that it presents detailed computer simulations for all models presented with explanations of the program code. It includes unique and distinctive chapters on disease diagnosis, telemedicine, medical imaging, smart health monitoring, social media healthcare, and machine learning for COVID-19. These chapters help develop a clear understanding of the working of an algorithm while strengthening logical thinking. In this environment, answering a single question may require accessing several data sources and calling on sophisticated analysis tools. While data integration is a dynamic research area in the database community, the specific needs of research have led to the development of numerous middleware systems that provide seamless data access in a result-driven environment. Since this book is intended to be useful to a wide audience, students, researchers and scientists from both academia and industry may all benefit from this material. It contains a comprehensive description of issues for healthcare data management and an overview of existing systems, making it appropriate for introductory and instructional purposes. Prerequisites are minimal; the readers are expected to have basic knowledge of machine learning. This book is divided into 22 real-time innovative chapters which provide a variety of application examples in different domains. These chapters illustrate why traditional approaches often fail to meet customers’ needs. The presented approaches provide a comprehensive overview of current technology. Each of these chapters, which are written by the main inventors of the presented systems, specifies requirements and provides a description of both the chosen approach and its implementation. Because of the self-contained nature of these chapters, they may be read in any order. Each of the chapters use various technical terms which involve expertise in machine learning and computer science.

Download or read book Proceedings of International Joint Conference on Computational Intelligence written by Mohammad Shorif Uddin and published by Springer. This book was released on 2019-07-03 with total page 728 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gathers outstanding research papers presented at the International Joint Conference on Computational Intelligence (IJCCI 2018), which was held at Daffodil International University on 14–15 December 2018. The topics covered include: collective intelligence, soft computing, optimization, cloud computing, machine learning, intelligent software, robotics, data science, data security, big data analytics, and signal and natural language processing.

Download or read book Skin Lesion Detection from Dermoscopic Images Using Convolutional Neural Networks written by Adrià Romero López and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The recent emergence of machine learning and deep learning methods for medical image analysis has enabled the development of intelligent medical imaging-based diagnosis systems that can assist physicians in making better decisions about a patient's health. In particular, skin imaging is a field where these new methods can be applied with a high rate of success. This thesis focuses on the problem of automatic skin lesion detection, particularly on melanoma detection, by applying semantic segmentation and classification from dermoscopic images using a deep learning based approach. For the first problem, a U-Net convolutional neural network architecture is applied for an accurate extraction of the lesion region. For the second problem, the current model performs a binary classification (benign versus malignant) that can be used for early melanoma detection. The model is general enough to be extended to multi-class skin lesion classification. The proposed solution is built around the VGG-Net ConvNet architecture and uses the transfer learning paradigm. Finally, this work performs a comparative evaluation of classification alone (using the entire image) against a combination of the two approaches (segmentation followed by classification) in order to assess which of them achieves better classification results. Experimental results for the classification task are encouraging: on the ISIC Archive dataset, the proposed method achieves an accuracy in the top three of the best previously published results. The experimental results of the segmentation evaluations demonstrate that the proposed method can outperform other state-of-the-art models.

Download or read book Data Analytics in Bioinformatics written by Rabinarayan Satpathy and published by John Wiley & Sons. This book was released on 2021-01-20 with total page 433 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning techniques are increasingly being used to address problems in computational biology and bioinformatics. Novel machine learning computational techniques to analyze high throughput data in the form of sequences, gene and protein expressions, pathways, and images are becoming vital for understanding diseases and future drug discovery. Machine learning techniques such as Markov models, support vector machines, neural networks, and graphical models have been successful in analyzing life science data because of their capabilities in handling randomness and uncertainty of data noise and in generalization. Machine Learning in Bioinformatics compiles recent approaches in machine learning methods and their applications in addressing contemporary problems in bioinformatics approximating classification and prediction of disease, feature selection, dimensionality reduction, gene selection and classification of microarray data and many more.