相关论文: Approximate Lesion Localization in Dermoscopy Imag…

Skin cancer is by far in top-3 of the world's most common cancer. Among different skin cancer types, melanoma is particularly dangerous because of its ability to metastasize. Early detection is the key to success in skin cancer treatment.…

This study focuses on automatic skin cancer detection using a Meta-learning approach for dermoscopic images. The aim of this study is to explore the benefits of the generalization of the knowledge extracted from non-medical data in the…

This paper reports the methods and techniques we have developed for classify dermoscopic images (task 1) of the ISIC 2019 challenge dataset for skin lesion classification, our approach aims to use ensemble deep neural network with some…

Melanoma, one of most dangerous types of skin cancer, re-sults in a very high mortality rate. Early detection and resection are two key points for a successful cure. Recent research has used artificial intelligence to classify melanoma and…

Burn injuries can result from mechanisms such as thermal, chemical, and electrical insults. A prompt and accurate assessment of burns is essential for deciding definitive clinical treatments. Currently, the primary approach for burn…

This chapter presents a methodology for diagnosis of pigmented skin lesions using convolutional neural networks. The architecture is based on convolu-tional neural networks and it is evaluated using new CNN models as well as re-trained…

Here, we report analysis and summary of research in the field of localization microscopy for optical imaging. We introduce the basic elements of super-resolved localization microscopy methods for PALM and STORM, commonly used both in vivo…

Malignant melanoma (MM) is one of the deadliest types of skin cancer. Analysing dermatoscopic images plays an important role in the early detection of MM and other pigmented skin lesions. Among different computer-based methods, deep…

Human face perception is currently an active research area in the computer vision community. Skin detection is one of the most important and primary stages for this purpose. So far, many approaches are proposed to done this case. Near all…

The potential of deep neural networks in skin lesion classification has already been demonstrated to be on-par if not superior to the dermatologists diagnosis. However, the performance of these models usually deteriorates when the test data…

Usually, lesions are not isolated but are associated with the surrounding tissues. For example, the growth of a tumour can depend on or infiltrate into the surrounding tissues. Due to the pathological nature of the lesions, it is…

The clinical diagnosis of skin lesion involves the analysis of dermoscopic and clinical modalities. Dermoscopic images provide a detailed view of the surface structures whereas clinical images offer a complementary macroscopic information.…

Automatic and accurate detection of anatomical landmarks is an essential operation in medical image analysis with a multitude of applications. Recent deep learning methods have improved results by directly encoding the appearance of the…

Deep learning-based melanoma classification with dermoscopic images has recently shown great potential in automatic early-stage melanoma diagnosis. However, limited by the significant data imbalance and obvious extraneous artifacts, i.e.,…

In this paper we propose a new approach to identify melanoma diseases by identifying the distribution of its main skin chromophores (melanin, oxyhemoglobin and deoxyhemoglobin) from multispectral dermatological images. Based on Blind Source…

The determination of precise skin lesion boundaries in dermoscopic images using automated methods faces many challenges, most importantly, the presence of hair, inconspicuous lesion edges and low contrast in dermoscopic images, and…

Importance: Machine learning (ML) approaches to facial landmark localization carry great clinical potential for quantitative assessment of facial function as they enable high-throughput automated quantification of relevant facial metrics…

Skin cancer is also one of the most common and dangerous types of cancer in the world that requires timely and precise diagnosis. In this paper, a deep-learning architecture of the multi-class skin lesion classification on the HAM10000…

Clinical dermatology necessitates precision and innovation for efficient diagnosis and treatment of various skin conditions. This paper introduces the development of a cutting-edge hyperspectral dermatoscope (the Hyperscope) tailored for…

Skin cancer is the most common human malignancy(American Cancer Society) which is primarily diagnosed visually, starting with an initial clinical screening and followed potentially by dermoscopic(related to skin) analysis, a biopsy and…