Results 31 to 40 of about 556 (209)

Rethinking Skin Lesion Segmentation in a Convolutional Classifier [PDF]

Journal of Digital Imaging, 2017
Melanoma is a fatal form of skin cancer when left undiagnosed. Computer-aided diagnosis systems powered by convolutional neural networks (CNNs) can improve diagnostic accuracy and save lives. CNNs have been successfully used in both skin lesion segmentation and classification. For reasons heretofore unclear, previous works have found image segmentation
Jack Burdick, Oge Marques, Janet Weinthal, Borko Furht   +3 more
openaire   +2 more sources

ANALYSES OF SKIN LESION AREAS AFTER THRESHOLDING

Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska, 2020
Melanoma is one of the fastest spreading cancers. The aim of the article is to segment the skin lesions from human skin dermatoscopic images covered by melanoma. Threshold segmentation was used, which allows a single skin lesion to be analyzed.
Magdalena Michalska
doaj   +1 more source

Attention-based dual-path feature fusion network for automatic skin lesion segmentation

BioData Mining, 2023
Automatic segmentation of skin lesions is a critical step in Computer Aided Diagnosis (CAD) of melanoma. However, due to the blurring of the lesion boundary, uneven color distribution, and low image contrast, resulting in poor segmentation result. Aiming
Zhenxiang He, Xiaoxia Li, Yuling Chen, Nianzu Lv, Yong Cai   +4 more
doaj   +1 more source

Semi-Supervised Skin Lesion Segmentation With Coupling CNN and Transformer Features

IEEE Access, 2022
An automatic skin lesion segmentation algorithm not only facilitates the dermatologist’s workload on skin cancer analysis but also provides a platform for early cancer prediction. Over the years, several deep learning methods have been proposed to
Mohammad D. Alahmadi, Wajdi Alghamdi
doaj   +1 more source

Guidelines for Pediatric Radiotherapy Simulation: A Report From the Children's Oncology Group Radiation Oncology Discipline

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Pediatric radiation therapy presents unique challenges compared to adult treatments, including those of immobilization, potential need for sedation, and the critical importance of accurate, reproducible positioning. Additionally, heightened attention to imaging doses is necessary to minimize long‐term toxicity in survivors.
Parham Alaei, Stephen Mihalcik, Sujith Baliga, Young Kwok, Dana Casey, Eric Ehler, Christiane Burton, John C. Breneman, Daphne A. Haas‐Kogan, Suzanne L. Wolden, Arnold C. Paulino, Nadia N. Laack, Natia Esiashvili, Sarah Milgrom, Christine Hill‐Kayser, Thomas J. Fitzgerald, John A. Kalapurakal, Chia‐Ho Hua   +17 more
wiley   +1 more source

A Deep Residual Architecture for Skin Lesion Segmentation

, 2018
In this paper, we propose an automatic approach to skin lesion region segmentation based on a deep learning architecture with multi-scale residual connections. The architecture of the proposed model is based on UNet [22] with residual connections to maximise the learning capability and performance of the network.
Gurram Munirathnam, Venkatesh, Yarlapati Ganesh, Naresh, Little, Suzanne, O'Connor, Noel E.   +3 more
openaire   +2 more sources

Clinical, Histopathological, and Molecular Characterization of Pediatric MN1::ZNF341‐Associated Cancer

Pediatric Blood &Cancer, EarlyView.
ABSTRACT A lethal round‐cell malignancy with an MN1::ZNF341 fusion has recently been reported in three infants. Here, we describe four further tumors, three in newborns (including monozygotic twins), and one in an adolescent. Detailed clinical, radiological, and histopathological data differentiate these tumors from their main mimics, neuroblastoma and
Thomas R. W. Oliver, Dyanne Rampling, Barbara Walkowiak, Nathaniel D. Anderson, Manas Dave, Henry Lee‐Six, Sadie Baskind, Pooja Balasubramanian, Glenn Anderson, Conor Parks, Toochi Ogbonnah, Emilia R. Robertson, Simon Hannam, Rohan Verma, John C. Achermann, Liina Palm, Neil Sebire, Thomas Jacques, Tom Watson, Carryl Dryden, Karin Straathof, Mette Jorgensen, Olga Slater, Sam Behjati, Sarita Depani, J. Ciaran Hutchinson   +25 more
wiley   +1 more source

CACDU-Net: A Novel DoubleU-Net Based Semantic Segmentation Model for Skin Lesions Detection in Images

IEEE Access, 2023
Skin lesion segmentation is a critical task in the field of dermatology as it can aid in the early detection and diagnosis of skin diseases. Deep learning techniques have shown great potential in achieving accurate lesion segmentation.
Shengnan Hao, Haotian Wu, Chengyuan Du, Xinyi Zeng, Zhanlin Ji, Xueji Zhang, Ivan Ganchev   +6 more
doaj   +1 more source

Impact of Metastatic Patterns on Survival and Response to Therapy in Neuroblastoma

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background While the presence of metastases in neuroblastoma (NB) is a well‐established prognostic factor, the clinical significance of dissemination patterns and tumour burden and their impact on response and survival remains poorly understood.
Mariona Morell‐Daniel, Santiago Pérez‐Hoyos, Aroa Soriano, Ana Coma, Amalia Varo, Raquel Hladun, Gabriela Guillén, Soraya Mico, Marta Garrido, Lourdes Rubio, Alba Rubio‐San‐Simón, Ana Minguez, Ricardo López‐Almaraz, Laura Illade, Miguel F. Segura, Lucas Moreno   +15 more
wiley   +1 more source

Exploring the Impact of Skin Color on Skin Lesion Segmentation

CoRR
Skin cancer, particularly melanoma, remains a major cause of morbidity and mortality, making early detection critical. AI-driven dermatology systems often rely on skin lesion segmentation as a preprocessing step to delineate the lesion from surrounding skin and support downstream analysis.
Kuniko Paxton, Medina Kapo, Amila Akagic, Koorosh Aslansefat, Dhavalkumar Thakker, Yiannis Papadopoulos   +5 more
openaire   +2 more sources