Cargando…
Brain Tumor Segmentation from MRI Images Using Handcrafted Convolutional Neural Network
Brain tumor segmentation from magnetic resonance imaging (MRI) scans is critical for the diagnosis, treatment planning, and monitoring of therapeutic outcomes. Thus, this research introduces a novel hybrid approach that combines handcrafted features with convolutional neural networks (CNNs) to enhan...
Autores principales: | Ullah, Faizan, Nadeem, Muhammad, Abrar, Mohammad, Al-Razgan, Muna, Alfakih, Taha, Amin, Farhan, Salam, Abdu |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10453895/ https://www.ncbi.nlm.nih.gov/pubmed/37627909 http://dx.doi.org/10.3390/diagnostics13162650 |
Ejemplares similares
-
Comparison of handcrafted features and convolutional neural networks for liver MR image adequacy assessment
por: Lin, Wenyi, et al.
Publicado: (2020) -
Automatic Left Ventricle Segmentation from Short-Axis Cardiac MRI Images Based on Fully Convolutional Neural Network
por: Shaaf, Zakarya Farea, et al.
Publicado: (2022) -
Deep Feature Fusion and Optimization-Based Approach for Stomach Disease Classification
por: Mohammad, Farah, et al.
Publicado: (2022) -
Automatic Analysis of MRI Images for Early Prediction of Alzheimer’s Disease Stages Based on Hybrid Features of CNN and Handcrafted Features
por: Khalid, Ahmed, et al.
Publicado: (2023) -
Framework to Detect Schizophrenia in Brain MRI Slices with Mayfly Algorithm-Selected Deep and Handcrafted Features
por: Manic, K. Suresh, et al.
Publicado: (2022)