Download or read book Automatic Segmentation of Skin Lesions from Dermatological Photographs written by Jeffrey Luc Glaister and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
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 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 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 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 Dermoscopic Image Segmentation Using Fuzzy Techniques written by Sowmya Devi and published by LAP Lambert Academic Publishing. This book was released on 2012 with total page 64 pages. Available in PDF, EPUB and Kindle. Book excerpt: Medical image segmentation is the most essential and crucial process in order to facilitate the characterization and visualization of the structure of interest in medical images. This work explains the task of segmenting skin lesions in Dermoscopy images using various Fuzzy clustering techniques for the early diagnosis of Malignant Melanoma. Malignant Melanoma is the most frequent type of skin cancer and its incidence has been rapidly increasing over the last few decades. Dermoscopy is a non-invasive diagnosis technique for the observation of pigmented skin lesions used in dermatology. Dermoscopic images have great potential in the early diagnosis of malignant melanoma, but their interpretation is time consuming and subjective, even for trained dermatologists.The various Fuzzy clustering techniques used are Fuzzy C Means Algorithm (FCM), Possibilistic C Means Algorithm and Hierarchical C Means Algorithm. The segmented images are compared with the ground truth image using various parameters such as False Positive Error (FPE), False Negative Error (FNE), Coefficient of similarity, Spatial overlap and their performance is evaluated
Download or read book Medical Content Based Retrieval for Clinical Decision Support written by Barbara Caputo and published by Springer Science & Business Media. This book was released on 2010-02-15 with total page 130 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the first MICCAI Workshop on Medical Content-Based Retrieval for Clinical Decision Support, MCBR_CBS 2009, held in London, UK, in September 2009. The 10 revised full papers were carefully reviewed and selected from numerous submissions. The papers are divide on several topics on medical image retrieval, clinical decision making and multimodal fusion.
Download or read book High accuracy Skin Lesion Segmentation and Size Determination written by Jae Won Shin and published by . This book was released on 2011 with total page 41 pages. Available in PDF, EPUB and Kindle. Book excerpt: Melanoma is one of the most common skin cancers. 5% of all cancer cases that occur in a year are cases of skin cancer and many people die each year by melanoma because of late recognition. Moreover, the number of new cases of melanoma in the United States has been increasing for at least 30 years. Fortunately, this melanoma is highly curable if it is detected early. In order to detect skin lesions, the automated skin lesion segmentation and diagnosis system on the Android system is an outstanding program to use. In this thesis, there are 4 functionalities, which include: camera data collecting, image processing, feature calculation, and classification. With these processes, an image is captured and is converted to a grey image. After a grey image is created, a skin lesion contour is found by OpenCV functions, cvFindContour() and cvWatershed(). When the contour is found, the features color, shape, and size of the lesion are extracted in order to classify whether the lesion is benign or malignant by using the KNN classifier. The goals and achievements of this thesis are to implement a function that captures images with the Android using camera properties, improve image segmentation and size estimation based on the previous prototype system on the Android platform with OpenCV. An image can be captured by a capturing function in this thesis and can be saved in a jpg file and a data xml file, which are used for image processing and camera features. In image processing, the watershed function is used instead of cvThreshold function, which is on the previous prototype system, so that the number for the threshold value is no more needed and the system can find the most method contour instead of finding several contours as it does in the previous system. In size estimation, two methods, which are reference method and camera distance method, are used. Reference method is when the system can estimate the area of a lesion by comparing reference pixels and lesion pixels. Camera distance method is when the system can estimate the area of a lesion according to camera distance properties, which are near, optimal, and far camera distance values. With these two methods, the system can estimate real area of a lesion without rulers instead of counting the number of pixels. Contour detection is improved to 98%. Reference size estimation and camera focus distance size estimations are 1.04% and 8.23%
Download or read book Region Adjacency Graph Approach for Acral Melanocytic Lesion Segmentation written by Joanna Jaworek-Korjakowska and published by Infinite Study. This book was released on with total page 14 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Digital Future of Healthcare written by Nilanjan Dey and published by CRC Press. This book was released on 2021-11-23 with total page 219 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on the applications of different digital platforms in the field of healthcare. It describes different devices used in digital healthcare, their benefits, diagnosis, use in treatment, and use cases related to mobile healthcare. Further, it covers machine and deep learning, blockchain technology, big data analytics as relevant to digital healthcare, telehealth technology, and digital applications in the field of push-and-pull pharma marketing. Overall, it enables readers to understand the basics of decision-making processes using digital techniques for the healthcare field. Features: Discusses various aspects of digitization of healthcare systems Examines deployment of machine learning including IoT and medical analytics Provides studies on the design, implementation, development, and management of intelligent healthcare systems Includes sensor-based digitization of healthcare data Reviews real-time advancement and challenges of digital communication in the field of healthcare This book is aimed at researchers and graduate students in healthcare, internet of things, machine learning, computer science, robotics, wearables, electrical engineering, and biomedical engineering.
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 Automatic Segmentation and Measurement of Lesions from Brain Images written by Shan Yu and published by . This book was released on 1995 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt:
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 Imaging in Dermatology written by Michael R. Hamblin and published by Academic Press. This book was released on 2016-07-29 with total page 562 pages. Available in PDF, EPUB and Kindle. Book excerpt: Imaging in Dermatology covers a large number of topics in dermatological imaging, the use of lasers in dermatology studies, and the implications of using these technologies in research. Written by the experts working in these exciting fields, the book explicitly addresses not only current applications of nanotechnology, but also discusses future trends of these ever-growing and rapidly changing fields, providing clinicians and researchers with a clear understanding of the advantages and challenges of laser and imaging technologies in skin medicine today, along with the cellular and molecular effects of these technologies. - Outlines the fundamentals of imaging and lasers for dermatology in clinical and research settings - Provides knowledge of current and future applications of dermatological imaging and lasers - Coherently structured book written by the experts working in the fields covered
Download or read book Measuring Surface Area of Skin Lesions with 2D and 3D Algorithms written by Houman Mirzaalian Dastjerdi and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: Purpose. The treatment of skin lesions of various kinds is a common task in clinical routine. Apart from wound care, the assessment of treatment efficacy plays an important role. In this paper, we present a new approach to measure the skin lesion surface in two and three dimensions. Methods. For the 2D approach, a single photo containing a flexible paper ruler is taken. After semi-automatic segmentation of the lesion, evaluation is based on local scale estimation using the ruler. For the 3D approach, reconstruction is based on Structure from Motion. Roughly outlining the region of interest around the lesion is required for both methods. Results. The measurement evaluation was performed on 117 phantom images and five phantom videos for 2D and 3D approach, respectively. We found an absolute error of 0.991.18 and a relative error 9.89 9.31% for 2D. These errors are and % for five test phantoms in our 3D case. As expected, the error of 2D surface area measurement increased by approximately 10% for wounds on the bent surface compared to wounds on the flat surface. Using our method, the only user interaction is to roughly outline the region of interest around the lesion. Conclusions. We developed a new wound segmentation and surface area measurement technique for skin lesions even on a bent surface. The 2D technique provides the user with a fast, user-friendly segmentation and measurement tool with reasonable accuracy for home care assessment of treatment. For 3D only preliminary results could be provided. Measurements were only based on phantoms and have to be repeated with real clinical data
Download or read book Color Medical Image Analysis written by M. Emre Celebi and published by Springer Science & Business Media. This book was released on 2012-09-16 with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since the early 20th century, medical imaging has been dominated by monochrome imaging modalities such as x-ray, computed tomography, ultrasound, and magnetic resonance imaging. As a result, color information has been overlooked in medical image analysis applications. Recently, various medical imaging modalities that involve color information have been introduced. These include cervicography, dermoscopy, fundus photography, gastrointestinal endoscopy, microscopy, and wound photography. However, in comparison to monochrome images, the analysis of color images is a relatively unexplored area. The multivariate nature of color image data presents new challenges for researchers and practitioners as the numerous methods developed for monochrome images are often not directly applicable to multichannel images. The goal of this volume is to summarize the state-of-the-art in the utilization of color information in medical image analysis.
Download or read book Computer Vision ECCV 2016 written by Bastian Leibe and published by Springer. This book was released on 2016-09-16 with total page 910 pages. Available in PDF, EPUB and Kindle. Book excerpt: The eight-volume set comprising LNCS volumes 9905-9912 constitutes the refereed proceedings of the 14th European Conference on Computer Vision, ECCV 2016, held in Amsterdam, The Netherlands, in October 2016. The 415 revised papers presented were carefully reviewed and selected from 1480 submissions. The papers cover all aspects of computer vision and pattern recognition such as 3D computer vision; computational photography, sensing and display; face and gesture; low-level vision and image processing; motion and tracking; optimization methods; physics-based vision, photometry and shape-from-X; recognition: detection, categorization, indexing, matching; segmentation, grouping and shape representation; statistical methods and learning; video: events, activities and surveillance; applications. They are organized in topical sections on detection, recognition and retrieval; scene understanding; optimization; image and video processing; learning; action, activity and tracking; 3D; and 9 poster sessions.
