Selection of Gradient Descent Optimizers for Convolutional Neural Network Based Brain Tumor Detectors

A Chatterjee, SS Mohanty, SK Mishra… - 2021 IEEE 2nd …, 2021 - ieeexplore.ieee.org
These days, brain tumor discovery has turned up as an overall causality in the domain of
medical care. The venture for tumor location begins with the procurement of MRI check …

A model of tumor growth coupling a cellular biomodel with biomechanical simulations

F Rikhtegar, E Kolokotroni… - Proceedings of the …, 2014 - ieeexplore.ieee.org
The aim of this paper is to present the development of a multi-scale and multiphysics
approach to tumor growth. An existing biomodel used for clinical tumor growth and response …

Multi-atlas patch-based segmentation and synthesis of brain tumor MR images

N Cordier - 2015 - theses.hal.science
This thesis focuses on the development of automatic methods for the segmentation and
synthesis of brain tumor Magnetic Resonance images. The main clinical perspective of …

Non rigid image registration by modeling deformations as elastic waves

S Ahmad, MF Khan - 2014 IEEE International Conference on …, 2014 - ieeexplore.ieee.org
In this paper we propose an inter-subject non-rigid image registration method that is derived
from the concept of elastodynamics. Non-rigid warps are modeled as elastic waves which …

An Non-Invasive Brain Disease Detection Using Deep Learning Techniques

PK Poonguzhali, A Murugarajan - 2022 - researchsquare.com
Brain tumours, the most common and hostile illness, have a relatively low survival rate
during their most mature stage. As a result, therapeutic planning is a critical stage in raising …

Brain tumor segmentation using convolutional neural network

PNS Jyothi, G Ajay, S Rohan, S Bhutada - World Journal of Advanced …, 2022 - wjarr.com
Nowadays health is an essential factor in human life, among all the health complexities
brain tumors are very critical to deal with. Though there are some existing techniques to …

[PDF][PDF] Development of 3-stage hybrid computer aided design (3-HCAD) system for multi-modal medical images to identify brain tumor

A Vajravelu, KS Tamilselvan, M Mahadi, WSBW Zaki… - pdfs.semanticscholar.org
The latest developments in medical imaging and computeraided solutions for image
processing problems attract attention of various researchers to impart their research in the …

Classification of Brain Tumor by Convolution Neural Networks

M Pallod, MV Vaidya - … for Competitive Strategies (ICTCS 2020) Intelligent …, 2021 - Springer
Brain tumors are problematic, leading to the highest degree of very low life span. Recovery
planning therefore represents a critical step toward improving patients' quality of life …

[PDF][PDF] A detailed survey on brain tumor detection using classification and optimization techniques

C Moorthy, KR Aravind Britto, R Vimala… - Int J Adv Sci …, 2020 - researchgate.net
The death due to cancer is formed at the ending stage of the cancer severity. Hence, the
detection of these cancers at a starting or primary stage is essential for preventing the …

[PDF][PDF] Review on Multiple Cancer Disease Prediction And Identification using Machine Learning Techniques

BS Jakkanwar, J Rohankar, S Bagde - academia.edu
Cancer has been described as a diverse illness with a wide range of subgroups. Early
cancer diagnosis and prognosis are essential for clinical patient treatment, which has …