A survey and analysis on automated glioma brain tumor segmentation and overall patient survival prediction
RR Agravat, MS Raval - Archives of Computational Methods in …, 2021 - Springer
Glioma is the deadliest brain tumor with high mortality. Treatment planning by human
experts depends on the proper diagnosis of physical symptoms along with Magnetic …
experts depends on the proper diagnosis of physical symptoms along with Magnetic …
Object detection using deep neural networks
M Shah, R Kapdi - 2017 International Conference on Intelligent …, 2017 - ieeexplore.ieee.org
The problem discussed in this article is object detection using deep neural network
especially convolution neural networks. Object detection was previously done using only …
especially convolution neural networks. Object detection was previously done using only …
Deep learning for automated brain tumor segmentation in mri images
RR Agravat, MS Raval - Soft computing based medical image analysis, 2018 - Elsevier
Early detection of a brain tumor increases life expectancy and survival chances of a patient.
Experts use modalities like magnetic resonance imaging (MRI) and computerized …
Experts use modalities like magnetic resonance imaging (MRI) and computerized …
Prediction of overall survival of brain tumor patients
RR Agravat, MS Raval - TENCON 2019-2019 IEEE Region 10 …, 2019 - ieeexplore.ieee.org
Automated brain tumor segmentation plays an important role in the diagnosis and prognosis
of the patient. In addition, features from the tumorous brain help in predicting patients' overall …
of the patient. In addition, features from the tumorous brain help in predicting patients' overall …
Research on road extraction from high-resolution remote sensing images based on improved UNet++
K Li, M Tan, D Xiao, T Yu, YF Li, J Li - IEEE Access, 2024 - ieeexplore.ieee.org
To address the challenges of road extraction in high-resolution remote sensing images, this
paper presents an enhanced UNet++ road extraction method that incorporates CBAM. The …
paper presents an enhanced UNet++ road extraction method that incorporates CBAM. The …
An Automated Segmentation and Counting of Ki67 Cells in Meningioma Using K-Means Clustering Technique
Meningioma is a type of primary brain tumours. The meningiomas account for about one-
third of all primary brain tumours. Image segmentation plays an important role in image …
third of all primary brain tumours. Image segmentation plays an important role in image …