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 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 A Novel Skin Lesion Detection Approach Using Neutrosophic Clustering and Adaptive Region Growing in Dermoscopy Images written by Yanhui Guo and published by Infinite Study. This book was released on with total page 19 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book 2017 13th IASTED International Conference on Biomedical Engineering BioMed written by IEEE Staff and published by . This book was released on 2017-02-20 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The topics of interest to be covered by BioMed 2017 include, but are not limited to BIOINFORMATICS AND COMPUTATIONAL BIOLOGY, BIOMATERIALS AND TISSUE ENGINEERING, BIOMECHANICS, BIOMEDICAL SENSORS AND INSTRUMENTATION, MEDICAL IMAGING AND SIGNAL PROCESSING, MEDICAL, REHABILITATION ROBOTICS AND ASSISTIVE TECHNOLOGY
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 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 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 A novel optimized neutrosophic k means using genetic algorithm for skin lesion detection in dermoscopy images written by Amira S. Ashour and published by Infinite Study. This book was released on with total page 9 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper implemented a new skin lesion detection method based on the genetic algorithm (GA) for optimizing the neutrosophic set (NS) operation to reduce the indeterminacy on the dermoscopy images.
Download or read book Statistical Atlases and Computational Models of the Heart Multi Sequence CMR Segmentation CRT EPiggy and LV Full Quantification Challenges written by Mihaela Pop and published by Springer Nature. This book was released on 2020-01-22 with total page 426 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed post-workshop proceedings of the 10th International Workshop on Statistical Atlases and Computational Models of the Heart: Atrial Segmentation and LV Quantification Challenges, STACOM 2019, held in conjunction with MICCAI 2019, in Shenzhen, China, in October 2019. The 42 revised full workshop papers were carefully reviewed and selected from 76 submissions. The topics of the workshop included: cardiac imaging and image processing, machine learning applied to cardiac imaging and image analysis, atlas construction, statistical modelling of cardiac function across different patient populations, cardiac computational physiology, model customization, atlas based functional analysis, ontological schemata for data and results, integrated functional and structural analyses, as well as the pre-clinical and clinical applicability of these methods.
Download or read book KI 2020 Advances in Artificial Intelligence written by Ute Schmid and published by Springer Nature. This book was released on 2020-09-08 with total page 367 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 43rd German Conference on Artificial Intelligence, KI 2020, held in Bamberg, Germany, in September 2020. The 16 full and 12 short papers presented together with 6 extended abstracts in this volume were carefully reviewed and selected from 62 submissions. As well-established annual conference series KI is dedicated to research on theory and applications across all methods and topic areas of AI research. KI 2020 had a special focus on human-centered AI with highlights on AI and education and explainable machine learning. Due to the Corona pandemic KI 2020 was held as a virtual event.
Download or read book Intelligent Computing written by Kohei Arai and published by Springer. This book was released on 2019-06-22 with total page 1127 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the proceedings of the Computing Conference 2019, providing a comprehensive collection of chapters focusing on core areas of computing and their real-world applications. Computing is an extremely broad discipline, encompassing a range of specialized fields, each focusing on particular areas of technology and types of application, and the conference offered pioneering researchers, scientists, industrial engineers, and students from around the globe a platform to share new ideas and development experiences. Providing state-of-the-art intelligent methods and techniques for solving real- world problems, the book inspires further research and technological advances in this important area.
Download or read book Context Aware Systems and Applications written by Phan Cong Vinh and published by Springer. This book was released on 2022-01-07 with total page 337 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed post-conference proceedings of the International Conference on Context-Aware Systems and Applications, held in October 2021. Due to COVID-19 pandemic the conference was held virtually. The 25 revised full papers presented were carefully selected from 52 submissions. The papers cover a wide spectrum of modern approaches and techniques for smart computing systems and their applications.
Download or read book Biomedical Data Mining for Information Retrieval written by Sujata Dash and published by John Wiley & Sons. This book was released on 2021-08-24 with total page 450 pages. Available in PDF, EPUB and Kindle. Book excerpt: BIOMEDICAL DATA MINING FOR INFORMATION RETRIEVAL This book not only emphasizes traditional computational techniques, but discusses data mining, biomedical image processing, information retrieval with broad coverage of basic scientific applications. Biomedical Data Mining for Information Retrieval comprehensively covers the topic of mining biomedical text, images and visual features towards information retrieval. Biomedical and health informatics is an emerging field of research at the intersection of information science, computer science, and healthcare and brings tremendous opportunities and challenges due to easily available and abundant biomedical data for further analysis. The aim of healthcare informatics is to ensure the high-quality, efficient healthcare, better treatment and quality of life by analyzing biomedical and healthcare data including patient’s data, electronic health records (EHRs) and lifestyle. Previously, it was a common requirement to have a domain expert to develop a model for biomedical or healthcare; however, recent advancements in representation learning algorithms allows us to automatically to develop the model. Biomedical image mining, a novel research area, due to the vast amount of available biomedical images, increasingly generates and stores digitally. These images are mainly in the form of computed tomography (CT), X-ray, nuclear medicine imaging (PET, SPECT), magnetic resonance imaging (MRI) and ultrasound. Patients’ biomedical images can be digitized using data mining techniques and may help in answering several important and critical questions relating to healthcare. Image mining in medicine can help to uncover new relationships between data and reveal new useful information that can be helpful for doctors in treating their patients. Audience Researchers in various fields including computer science, medical informatics, healthcare IOT, artificial intelligence, machine learning, image processing, clinical big data analytics.
Download or read book Machine Learning in Medical Imaging written by Mingxia Liu and published by Springer Nature. This book was released on 2020-10-02 with total page 702 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 11th International Workshop on Machine Learning in Medical Imaging, MLMI 2020, held in conjunction with MICCAI 2020, in Lima, Peru, in October 2020. The conference was held virtually due to the COVID-19 pandemic. The 68 papers presented in this volume were carefully reviewed and selected from 101 submissions. They focus on major trends and challenges in the above-mentioned area, aiming to identify new-cutting-edge techniques and their uses in medical imaging. Topics dealt with are: deep learning, generative adversarial learning, ensemble learning, sparse learning, multi-task learning, multi-view learning, manifold learning, and reinforcement learning, with their applications to medical image analysis, computer-aided detection and diagnosis, multi-modality fusion, image reconstruction, image retrieval, cellular image analysis, molecular imaging, digital pathology, etc.
Download or read book Dermoscopy in General Dermatology written by Aimilios Lallas and published by CRC Press. This book was released on 2018-09-03 with total page 719 pages. Available in PDF, EPUB and Kindle. Book excerpt: This lavishly illustrated guide from experts will enable practitioners to get the most out of dermoscopy for investigations and treatments in general dermatology.
Download or read book Advances in Integrations of Intelligent Methods written by Ioannis Hatzilygeroudis and published by Springer Nature. This book was released on 2020-01-17 with total page 171 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a number of research efforts in combining AI methods or techniques to solve complex problems in various areas. The combination of different intelligent methods is an active research area in artificial intelligence (AI), since it is believed that complex problems can be more easily solved with integrated or hybrid methods, such as combinations of different soft computing methods (fuzzy logic, neural networks, and evolutionary algorithms) among themselves or with hard AI technologies like logic and rules; machine learning with soft computing and classical AI methods; and agent-based approaches with logic and non-symbolic approaches. Some of the combinations are already extensively used, including neuro-symbolic methods, neuro-fuzzy methods, and methods combining rule-based and case-based reasoning. However, other combinations are still being investigated, such as those related to the semantic web, deep learning and swarm intelligence algorithms. Most are connected with specific applications, while the rest are based on principles.
Download or read book Advances in Visual Informatics written by Halimah Badioze Zaman and published by Springer Nature. This book was released on 2019-11-12 with total page 760 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 6th International Conference on Advances in Visual Informatics, IVIC 2019, held in Bangi, Malaysia, in November 2019. The 65 papers presented were carefully reviewed and selected from 130 submissions. The papers are organized into the following topics: Visualization and Digital Innovation for Society 5.0; Engineering and Digital Innovation for Society 5.0; Cyber Security and Digital Innovation for Society 5.0; and Social Informatics and Application for Society 5.0.
