Cargando…
Conditional Random Fields and Supervised Learning in Automated Skin Lesion Diagnosis
Many subproblems in automated skin lesion diagnosis (ASLD) can be unified under a single generalization of assigning a label, from an predefined set, to each pixel in an image. We first formalize this generalization and then present two probabilistic models capable of solving it. The first model is...
Autores principales: | Wighton, Paul, Lee, Tim K., Mori, Greg, Lui, Harvey, McLean, David I., Atkins, M. Stella |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2011
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3199211/ https://www.ncbi.nlm.nih.gov/pubmed/22046177 http://dx.doi.org/10.1155/2011/846312 |
Ejemplares similares
-
Deep echocardiography: data-efficient supervised and semi-supervised deep learning towards automated diagnosis of cardiac disease
por: Madani, Ali, et al.
Publicado: (2018) -
Automated lesion detection on MRI scans using combined unsupervised and supervised methods
por: Guo, Dazhou, et al.
Publicado: (2015) -
Rapid diagnosis of hereditary haemolytic anaemias using automated rheoscopy and supervised machine learning
por: Moura, Pedro L., et al.
Publicado: (2020) -
Automated Skin Lesion Classification on Ultrasound Images
por: Marosán-Vilimszky , Péter, et al.
Publicado: (2021) -
Long-Range Diagnosis of and Support for Skin Conditions in Field Settings
por: Williams, Victoria, et al.
Publicado: (2018)