Cargando…
Refining skin lesions classification performance using geometric features of superpixels
This paper introduces superpixels to enhance the detection of skin lesions and to discriminate between melanoma and nevi without false negatives, in dermoscopy images. An improved Simple Linear Iterative Clustering (iSLIC) superpixels algorithm for image segmentation in digital image processing is p...
Autores principales: | Moldovanu, Simona, Miron, Mihaela, Rusu, Cristinel-Gabriel, Biswas, Keka C., Moraru, Luminita |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10349833/ https://www.ncbi.nlm.nih.gov/pubmed/37454166 http://dx.doi.org/10.1038/s41598-023-38706-5 |
Ejemplares similares
-
Skin Lesion Classification Based on Surface Fractal Dimensions and Statistical Color Cluster Features Using an Ensemble of Machine Learning Techniques
por: Moldovanu, Simona, et al.
Publicado: (2021) -
Towards Accurate Diagnosis of Skin Lesions Using Feedforward Back Propagation Neural Networks
por: Moldovanu, Simona, et al.
Publicado: (2021) -
Combining Sparse and Dense Features to Improve Multi-Modal Registration for Brain DTI Images
por: Moldovanu, Simona, et al.
Publicado: (2020) -
Superpixel-Oriented Label Distribution Learning for Skin Lesion Segmentation
por: Zhou, Qiaoer, et al.
Publicado: (2022) -
Entropy Rate Superpixel Classification for Automatic Red Lesion Detection in Fundus Images
por: Romero-Oraá, Roberto, et al.
Publicado: (2019)