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Artificial Intelligence dermoscopy

Anna-Marie Hosking, Brandon J Coakley, Dorothy Chang, Faezeh Talebi-Liasi, Samantha Lish, Sung Won Lee, Amanda M Zong, Ian Moore, James Browning, Steven L Jacques, James G Krueger, Kristen M Kelly, Kenneth G Linden, Daniel S Gareau
OBJECTIVES: Early melanoma detection decreases morbidity and mortality. Early detection classically involves dermoscopy to identify suspicious lesions for which biopsy is indicated. Biopsy and histological examination then diagnose benign nevi, atypical nevi, or cancerous growths. With current methods, a considerable number of unnecessary biopsies are performed as only 11% of all biopsied, suspicious lesions are actually melanomas. Thus, there is a need for more advanced noninvasive diagnostics to guide the decision of whether or not to biopsy...
January 17, 2019: Lasers in Surgery and Medicine
Lavinia Ferrante di Ruffano, Yemisi Takwoingi, Jacqueline Dinnes, Naomi Chuchu, Susan E Bayliss, Clare Davenport, Rubeta N Matin, Kathie Godfrey, Colette O'Sullivan, Abha Gulati, Sue Ann Chan, Alana Durack, Susan O'Connell, Matthew D Gardiner, Jeffrey Bamber, Jonathan J Deeks, Hywel C Williams
BACKGROUND: Early accurate detection of all skin cancer types is essential to guide appropriate management and to improve morbidity and survival. Melanoma and cutaneous squamous cell carcinoma (cSCC) are high-risk skin cancers which have the potential to metastasise and ultimately lead to death, whereas basal cell carcinoma (BCC) is usually localised with potential to infiltrate and damage surrounding tissue. Anxiety around missing early curable cases needs to be balanced against inappropriate referral and unnecessary excision of benign lesions...
December 4, 2018: Cochrane Database of Systematic Reviews
Federica Bogo, Javier Romero, Enoch Peserico, Michael J Black
Detection of new or rapidly evolving melanocytic lesions is crucial for early diagnosis and treatment of melanoma. We propose a fully automated pre-screening system for detecting new lesions or changes in existing ones, on the order of 2 - 3mm, over almost the entire body surface. Our solution is based on a multi-camera 3D stereo system. The system captures 3D textured scans of a subject at different times and then brings these scans into correspondence by aligning them with a learned, parametric, non-rigid 3D body model...
2014: Medical Image Computing and Computer-assisted Intervention: MICCAI ..
Kouhei Shimizu, Hitoshi Iyatomi, M Emre Celebi, Kerri-Ann Norton, Masaru Tanaka
This paper proposes a new computer-aided method for the skin lesion classification applicable to both melanocytic skin lesions (MSLs) and nonmelanocytic skin lesions (NoMSLs). The computer-aided skin lesion classification has drawn attention as an aid for detection of skin cancers. Several researchers have developed methods to distinguish between melanoma and nevus, which are both categorized as MSL. However, most of these studies did not focus on NoMSLs such as basal cell carcinoma (BCC), the most common skin cancer and seborrheic keratosis (SK) despite their high incidence rates...
January 2015: IEEE Transactions on Bio-medical Engineering
I Ibraheem
BACKGROUND: Melanoma is a leading fatal illness responsible for 80% of deaths from skin cancer. It originates in the pigment-producing melanocytes in the basal layer of the epidermis. Melanocytes produce the melanin (the dark pigment), which is responsible for the color of skin. As all cancers, melanoma is caused by damage to the DNA of the cells, which causes the cell to grow out of control, leading to a tumor, which is much more dangerous if it cannot be found or detected early. Only biopsy can determine exact malformation diagnosis, although it can rise metastasizing...
February 2015: Skin Research and Technology
Wilhelm Stolz
No abstract text is available yet for this article.
July 2014: Journal der Deutschen Dermatologischen Gesellschaft: JDDG
Gang Zhang, Jian Yin, Xiangyang Su, Yongjing Huang, Yingrong Lao, Zhaohui Liang, Shanxing Ou, Honglai Zhang
Skin biopsy images can reveal causes and severity of many skin diseases, which is a significant complement for skin surface inspection. Automatic annotation of skin biopsy image is an important problem for increasing efficiency and reducing the subjectiveness in diagnosis. However it is challenging particularly when there exists indirect relationship between annotation terms and local regions of a biopsy image, as well as local structures with different textures. In this paper, a novel method based on a recent proposed machine learning model, named multi-instance multilabel (MIML), is proposed to model the potential knowledge and experience of doctors on skin biopsy image annotation...
2014: BioMed Research International
Ali Madooei, Mark S Drew, Maryam Sadeghi, M Stella Atkins
Skin lesions are often comprised of various colours. The presence of multiple colours with an irregular distribution can signal malignancy. Among common colours under dermoscopy, blue-grey (blue-white veil) is a strong indicator of malignant melanoma. Since it is not always easy to visually identify and recognize this feature, a computerised automatic colour analysis method can provide the clinician with an objective second opinion. In this paper, we put forward an innovative method, through colour analysis and computer vision techniques, to automatically detect and segment blue-white veil areas in dermoscopy images...
2013: Medical Image Computing and Computer-assisted Intervention: MICCAI ..
Jose Luis García Arroyo, Begoña García Zapirain
By means of this study, a detection algorithm for the "pigment network" in dermoscopic images is presented, one of the most relevant indicators in the diagnosis of melanoma. The design of the algorithm consists of two blocks. In the first one, a machine learning process is carried out, allowing the generation of a set of rules which, when applied over the image, permit the construction of a mask with the pixels candidates to be part of the pigment network. In the second block, an analysis of the structures over this mask is carried out, searching for those corresponding to the pigment network and making the diagnosis, whether it has pigment network or not, and also generating the mask corresponding to this pattern, if any...
January 2014: Computers in Biology and Medicine
Mohammad Taghi Bahreyni Toossi, Hamid Reza Pourreza, Hoda Zare, Mohamad-Hoseyn Sigari, Pouran Layegh, Abbas Azimi
BACKGROUND/PURPOSE: Dermoscopy is one of the major imaging modalities used in the diagnosis of pigmented skin lesions. Due to the difficulty and subjectivity of human interpretation, computerized image analysis techniques have become important tools in this research area. Hair removal from skin lesion images is one of the key problems for the precise segmentation and analysis of the skin lesions. In this study, we present a new scheme that automatically detects and removes hairs from dermoscopy images...
August 2013: Skin Research and Technology
Pelin Guvenc, Robert W LeAnder, Serkan Kefel, William V Stoecker, Ryan K Rader, Kristen A Hinton, Sherea M Stricklin, Harold S Rabinovitz, Margaret Oliviero, Randy H Moss
BACKGROUND: Blue-gray ovoids (B-GOs), a critical dermoscopic structure for basal cell carcinoma (BCC), offer an opportunity for automatic detection of BCC. Due to variation in size and color, B-GOs can be easily mistaken for similar structures in benign lesions. Analysis of these structures could afford accurate characterization and automatic recognition of B-GOs, furthering the goal of automatic BCC detection. This study utilizes a novel segmentation method to discriminate B-GOs from their benign mimics...
February 2013: Skin Research and Technology
Verena Ahlgrimm-Siess, Martin Laimer, Edith Arzberger, Rainer Hofmann-Wellenhof
Early detection of melanoma remains crucial to ensuring a favorable prognosis. Dermoscopy and total body photography are well-established noninvasive aids that increase the diagnostic accuracy of dermatologists in their daily routine, beyond that of a naked-eye examination. New noninvasive diagnostic techniques, such as reflectance confocal microscopy, multispectral digital imaging and RNA microarrays, are currently being investigated to determine their utility for melanoma detection. This review presents emerging technologies for noninvasive melanoma diagnosis, and discusses their advantages and limitations...
July 2012: Future Oncology
B Cheng, R J Stanley, W V Stoecker, K Hinton
BACKGROUND: Telangiectasia, tiny skin vessels, are important dermoscopy structures used to discriminate basal cell carcinoma (BCC) from benign skin lesions. This research builds off of previously developed image analysis techniques to identify vessels automatically to discriminate benign lesions from BCCs. METHODS: A biologically inspired reinforcement learning approach is investigated in an adaptive critic design framework to apply action-dependent heuristic dynamic programming (ADHDP) for discrimination based on computed features using different skin lesion contrast variations to promote the discrimination process...
November 2012: Skin Research and Technology
Qaisar Abbas, M Emre Celebi, Irene Fondón
BACKGROUND: Computer-aided pattern classification of melanoma and other pigmented skin lesions is one of the most important tasks for clinical diagnosis. To differentiate between benign and malignant lesions, the extraction of color, architectural order, symmetry of pattern and homogeneity (CASH) is a challenging task. METHODS: In this article, a novel pattern classification system (PCS) based on the clinical CASH rule is presented to classify among six classes of patterns...
August 2012: Skin Research and Technology
Kerri-Ann Norton, Hitoshi Iyatomi, M Emre Celebi, Sumiko Ishizaki, Mizuki Sawada, Reiko Suzaki, Ken Kobayashi, Masaru Tanaka, Koichi Ogawa
BACKGROUND: Computer-aided diagnosis of dermoscopy images has shown great promise in developing a quantitative, objective way of classifying skin lesions. An important step in the classification process is lesion segmentation. Many studies have been successful in segmenting melanocytic skin lesions (MSLs), but few have focused on non-melanocytic skin lesions (NoMSLs), as the wide variety of lesions makes accurate segmentation difficult. METHODS: We developed an automatic segmentation program for detecting borders of skin lesions in dermoscopy images...
August 2012: Skin Research and Technology
Paul Wighton, Tim K Lee, Harvey Lui, David I McLean, M Stella Atkins
We present a general model using supervised learning and MAP estimation that is capable of performing many common tasks in automated skin lesion diagnosis. We apply our model to segment skin lesions, detect occluding hair, and identify the dermoscopic structure pigment network. Quantitative results are presented for segmentation and hair detection and are competitive when compared to other specialized methods. Additionally, we leverage the probabilistic nature of the model to produce receiver operating characteristic curves, show compelling visualizations of pigment networks, and provide confidence intervals on segmentations...
July 2011: IEEE Transactions on Information Technology in Biomedicine
Huiyu Zhou, Gerald Schaefer, M Celebi, Hitoshi Iyatomi, Kerri-Ann Norton, Tangwei Liu, Faquan Lin
Accurate identification of lesion borders is an important task in the analysis of dermoscopy images since the extraction of skin lesion borders provides important cues for accurate diagnosis. Snakes have been used for segmenting a variety of medical imagery including dermoscopy, however, due to the compromise of internal and external energy forces they can lead to under- or over-segmentation problems. In this paper, we introduce a mean shift based gradient vector flow (GVF) snake algorithm that drives the internal/external energies towards the correct direction...
2010: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Eva Armengol
OBJECTIVE: Early diagnosis of melanoma is based on the ABCD rule which considers asymmetry, border irregularity, color variegation, and a diameter larger than 5mm as the characteristic features of melanomas. When a skin lesion presents these features it is excised as prevention. Using a non-invasive technique called dermoscopy, dermatologists can give a more accurate evaluation of skin lesions, and can therefore avoid the excision of lesions that are benign. However, dermatologists need to achieve a good dermatoscopic classification of lesions prior to extraction...
February 2011: Artificial Intelligence in Medicine
Paul Wighton, Maryam Sadeghi, Tim K Lee, M Stella Atkins
We present a method for automatically segmenting skin lesions by initializing the random walker algorithm with seed points whose properties, such as colour and texture, have been learnt via a training set. We leverage the speed and robustness of the random walker algorithm and augment it into a fully automatic method by using supervised statistical pattern recognition techniques. We validate our results by comparing the resulting segmentations to the manual segmentations of an expert over 120 cases, including 100 cases which are categorized as difficult (i...
2009: Medical Image Computing and Computer-assisted Intervention: MICCAI ..
Brian J Katz, Margaret Oliviero, Harold Rabinovitz
Dermoscopy has clearly had a profound impact on the clinical diagnosis of pigmented lesions. It has been shown not only to be useful in the early diagnosis of melanomas but also, more recently, for the diagnosis of nonpigmented cutaneous malignancies. In this article, the authors will briefly explore the evolution of the use of this diagnostic technique along with how dermoscopy may be best utilized with future technologies.
February 2010: Journal of Drugs in Dermatology: JDD
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