Showing all 4 results

Automated Brain Tumor Segmentation and Classification in MRI using YOLO-based Deep Learning

5,500.00
The aim of this research is to develop a more effective and efficient brain tumor segmentation system using the YOLOv11 architecture. The focus is on enhancing the accuracy and reliability of tumor identification in brain imaging, specifically through advanced segmentation techniques. By leveraging deep learning models, the study seeks to provide an automated solution for real-time tumor segmentation, assisting in clinical decision-making and early diagnosis.

Brain Tumor Identification and Classification of MRI images using deep learning techniques

5,500.00
Aim: To detect and identify the Brain Tumor using Deep-Learning techniques Ā Abstract: Brain is the controlling unit of human body.

Deep Learning Technique to detect Brain tumor disease using YOLOv8

5,500.00
Aim: The aim of this research is to develop a more effective and efficient brain tumor segmentation system using the YOLOv8 architecture.

DeepCurvMRI: Deep Convolutional Curvelet Transform-based MRI Approach for Early Detection of Alzheimerā€™s disease

5,500.00
Aim: Ā Ā Ā Ā Ā Ā Ā  To detect and identify the Alzheimers disease detection using Deep-Learning techniques Abstract: Ā Ā Ā Ā Ā  Alzheimer’s disease is a neurodegenerative