scholarly journals Multi-Class Skin Lesions Classification System Using Probability Map Based Region Growing and DCNN

2020 ◽  
Vol 13 (1) ◽  
pp. 77
Author(s):  
T. Sreekesh Namboodiri ◽  
A. Jayachandran
Keyword(s):  
Classification System ◽  
Region Growing ◽  
Skin Lesions ◽  
Probability Map

Detection and Classification of Skin Lesions using Probability Map-based Region Growing with BA-KNN Classifier (Preprint)

2021 ◽  
Author(s):  
Sivaraj S ◽  
Dr.R. Malmathanraj
Keyword(s):  
Skin Lesion ◽  
Region Growing ◽  
Skin Lesions ◽  
Classification Approach ◽  
Probability Map ◽  
Knn Classifier ◽  
Knn Classification ◽  
Pigmented Skin Lesions ◽  
Thresholding Algorithm

BACKGROUND Melanoma is one of the most hazardous existing diseases, and is a kind of threatening pigmented skin lesion. Appropriate automated diagnosis of skin lesions and the categorization of melanoma may be exceptionally enhancing premature identification of melanomas. OBJECTIVE However, Models of categorization based on deterministic skin lesion may influence multi-dimensional nonlinear problem provokes inaccurate and ineffective categorization. This research presents a novel hybrid BA-KNN classification approach for pigmented skin lesions in dermoscopy images. METHODS In the first step, the skin lesion is preprocessed via automatic preprocessing algorithm together with a fusion hair detection and removal strategy. Also, a new probability map based region growing and optimal thresholding algorithm is integrated in this system to enhance the rate of accuracy. RESULTS Moreover, to attain better efficacy, an estimate of ABCD as well as geometric features are considered during the feature extraction to describe the malignancy of the lesion. CONCLUSIONS The evaluation of the experiment reveals the efficiency of the proposed approach on dermoscopy images with better accuracy

SEGMENTATION OF DERMATOSCOPIC IMAGES USED FOR COMPUTER-AIDED DIAGNOSIS OF MELANOMA

2010 ◽  
Vol 10 (02) ◽  
pp. 213-223
Author(s):  
MHAMMED MESSADI ◽  
ABDELHAFID BESSAID ◽  
A. TALEB-AHMED
Keyword(s):  
Methodological Approach ◽  
Region Growing ◽  
Skin Lesions ◽  
Skin Tumor ◽  
Border Detection ◽  
Fast Approach ◽  
Malignant Skin ◽  
Pigmented Skin Lesions ◽  
Aided Diagnosis ◽  
Related Mortality

In this paper, a methodological approach to the segmentation of tumours skin lesions in dermoscopy images is presented. Melanoma is the most malignant skin tumor, growing in melanocytes, the cells responsible for pigmentation. This type of cancer is nowadays increasing rapidly, its related mortality rate increases by more modest and inversely proportional to the thickness of the tumor. This rate can be decreased by an earlier detection and better prevention. In dermatoscopic images, the segmentation is essential to characterize the information shape of the lesion and also to locate the tumor for analysis. In this domain, we have evaluated several techniques for the segmentation of dermatoscopic images. All these methods do not exactly separate the lesion from the background. In this work a fast approach in border detection of dermoscopy pigmented skin lesions images based on the region growing algorithm is presented. This method is tested on a set of 60 dermoscopy images. The obtained results show that the presented method achieves both fast and accurate border detection.

Wound Area Segmentation Using 4-D Probability Map and Superpixel Region Growing

2019 ◽  
Author(s):  
Topu Biswas ◽  
Mohammad Faizal Ahmad Fauzi ◽  
Fazly Salleh Abas ◽  
Rajasvaran Logeswaran ◽  
Harikrishna K.R. Nair
Keyword(s):  
Region Growing ◽  
Wound Area ◽  
Probability Map

scholarly journals Neural network classification system for pigmented skin neoplasms with preliminary hair removal in photographs

2021 ◽  
Vol 5 (45) ◽  
pp. 728-735
Author(s):  
P.A. Lyakhov ◽  
U.A. Lyakhova
Keyword(s):  
Neural Network ◽  
Classification System ◽  
Skin Neoplasms ◽  
Skin Lesions ◽  
Diagnostic Efficiency ◽  
Automated Classification ◽  
Neural Network Classification ◽  
Pigmented Lesions ◽  
Classification Of Images ◽  
Visual Diagnosis

The article proposes a neural network classification system for pigmented skin neoplasms with a preliminary processing stage to remove hair from the images. The main difference of the proposed system is the use of the stage of preliminary image processing to identify the location of the hair and their further removal. This stage allows you to prepare dermatoscopic images for further analysis in order to carry out automated classification and diagnosis of pigmented skin lesions. Modeling was carried out using the MatLAB R2020b software package on clinical dermatoscopic images from the international open archive ISIC Melanoma Project. The proposed system made it possible to increase the recognition accuracy of pigmented skin lesion images in 10 diagnostically important categories up to 80.81%. The use of the proposed system for the recognition and classification of images of dermatoscopic pigmented lesions by specialists will make it possible to increase the diagnostic efficiency in comparison with methods of visual diagnosis, and will also allow starting treatment at an earlier stage of the disease, which directly affects the survival and recovery rates for patients.

Fine Structural Alterations in Thyroid Follicular Cells (FC) and Changes in Serum Thyroxine Produced by Feeding Polychlorinated Biphenyl (PCB) to Rats

1977 ◽  
Vol 35 ◽  
pp. 498-499
Author(s):  
W.T. Collins ◽  
Charles C. Capen ◽  
Louis Kasza
Keyword(s):  
Feed Efficiency ◽  
Polychlorinated Biphenyl ◽  
Serum Proteins ◽  
Skin Lesions ◽  
Hepatic Necrosis ◽  
Ultrastructural Changes ◽  
Lymphoid Tissues ◽  
Heat Transfer Fluids ◽  
Thyroid Follicular Cells ◽  
Peripheral Metabolism

The widespread contamination of the environment with PCB, a compound used extensively by industry in hydraulic and heat transfer fluids as well as plasticizers and solvents in adhesives and sealants, has resulted in detectable tissue levels in a large portion of the human population, domestic animals, and wildlife. Intoxication with PCB produces severe hepatic necrosis, degeneration of lymphoid tissues and kidney, skin lesions, decreased reproductive performance, reduced feed efficiency, and decreased weight gain. PCB also has been reported to reduce the binding of thyroid hormone to serum proteins and enhance the peripheral metabolism of thyroxine with increased excretion of thyroxine-glucuronide in the bile (Bastomsky, Endocrinology 95: 1150-1155, 1974).The objectives of this investigation were (1) to investigate the histopathologic, histochemical, and ultrastructural changes in thyroid FC produced by the acute (4 week) and chronic (12 week) administration of low (50 ppm) and high (500 ppm) doses of PCB to rats, (2) to correlate these alterations to changes in serum immunoreactive thyroxine concentration, and (3) to investigate the persistence of the effects of PCB on the thyroid gland.

International Research and Variation in Views of Ethnicity

2012 ◽  
Vol 2 (2) ◽  
pp. 66-72
Author(s):  
Ella Inglebret ◽  
Amy Skinder-Meredith ◽  
Shana Bailey ◽  
Carla Jones ◽  
Ashley France
Keyword(s):  
United States ◽  
Classification System ◽  
International Research ◽  
The United States ◽  
Research Articles ◽  
Journal Articles ◽  
Research Participants ◽  
The Past ◽  
International Scale ◽  
Publication Patterns

The authors in this article first identify the extent to which research articles published in three American Speech-Language-Hearing Association (ASHA) journals included participants, age birth to 18 years, from international backgrounds (i.e., residence outside of the United States), and go on to describe associated publication patterns over the past 12 years. These patterns then provide a context for examining variation in the conceptualization of ethnicity on an international scale. Further, the authors examine terminology and categories used by 11 countries where research participants resided. Each country uses a unique classification system. Thus, it can be expected that descriptions of the ethnic characteristics of international participants involved in research published in ASHA journal articles will widely vary.

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