Cargando…
Skin Lesion Classification Based on Surface Fractal Dimensions and Statistical Color Cluster Features Using an Ensemble of Machine Learning Techniques
SIMPLE SUMMARY: This study aimed to investigate the efficacy of implementation of novel skin surface fractal dimension features as an auxiliary diagnostic method for melanoma recognition. We therefore examined the skin lesion classification accuracy of the kNN-CV algorithm and of the proposed Radial...
Autores principales: | Moldovanu, Simona, Damian Michis, Felicia Anisoara, Biswas, Keka C., Culea-Florescu, Anisia, Moraru, Luminita |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8582408/ https://www.ncbi.nlm.nih.gov/pubmed/34771421 http://dx.doi.org/10.3390/cancers13215256 |
Ejemplares similares
-
Refining skin lesions classification performance using geometric features of superpixels
por: Moldovanu, Simona, et al.
Publicado: (2023) -
Towards Accurate Diagnosis of Skin Lesions Using Feedforward Back Propagation Neural Networks
por: Moldovanu, Simona, et al.
Publicado: (2021) -
A New Approach in Detectability of Microcalcifications in the Placenta during Pregnancy Using Textural Features and K-Nearest Neighbors Algorithm
por: Miron, Mihaela, et al.
Publicado: (2022) -
Combining Sparse and Dense Features to Improve Multi-Modal Registration for Brain DTI Images
por: Moldovanu, Simona, et al.
Publicado: (2020) -
Enhanced detonators detection in X-ray baggage inspection by image manipulation and deep convolutional neural networks
por: Oulhissane, Lynda, et al.
Publicado: (2023)