Brain Tumor

Brain tumor research focuses on improving the accuracy and efficiency of diagnosis and treatment planning, primarily using magnetic resonance imaging (MRI). Current research emphasizes the development of sophisticated deep learning models, including convolutional neural networks (CNNs), vision transformers, and hybrid architectures incorporating attention mechanisms, to analyze multi-modal MRI data and perform tasks such as tumor segmentation and classification. These advancements aim to improve diagnostic accuracy, personalize treatment strategies, and ultimately enhance patient outcomes, impacting both clinical practice and the broader medical imaging field.

Papers

June 4, 2022

Modeling of Textures to Predict Immune Cell Status and Survival of Brain Tumour Patients
Ahmad Chaddad, Mingli Zhang, Lama Hassan, Tamim Niazi
Radiomics Feature Brain Tumor Imaging Technique Deep Survival Texture Quality Imaging Data Blood Biomarkers

June 2, 2022

Examining the behaviour of state-of-the-art convolutional neural networks for brain tumor detection with and without transfer learning
Md. Atik Ahamed, Rabeya Tus Sadia
Convolutional Neural Network Transfer Learning Supervised ImageNet State of the Art Binary Classification BEHAVIOR Explanation Brain Tumor Multi Class Brain Tumor Detection

April 29, 2022

Preoperative brain tumor imaging: models and software for segmentation and standardized reporting
D. Bouget, A. Pedersen, A. S. Jakola, V. Kavouridis, K. E. Emblem, R. S. Eijgelaar, I. Kommers, H. Ardon, F. Barkhof, L. Bello, M. S. Berger, M. C. Nibali, J. Furtner, S. Hervey-Jumper, A. J. S. Idema, B. Kiesel, A. Kloet, E. Mandonnet, D. M. J. Müller, P. A. Robe, M. Rossi, T. Sciortino, W. Van den Brink, M. Wagemakers, G. Widhalm, M. G. Witte, A. H. Zwinderman, P. C. De Witt Hamer, O. Solheim, I. Reinertsen
Full Model Tumor Segmentation Brain Tumor Software System Tumor Detection Health Metric Surgical Video Segmentation Structured Reporting

April 26, 2022

Brain Tumor Detection and Classification Using a New Evolutionary Convolutional Neural Network
Amin Abdollahi Dehkordi, Mina Hashemi, Mehdi Neshat, Seyedali Mirjalili, Ali Safaa Sadiq
Classification Code Brain Tumor Brain MRI Brain Tumor Detection Brain MR Image

April 4, 2022

A Novel Mask R-CNN Model to Segment Heterogeneous Brain Tumors through Image Subtraction
Sanskriti Singh
Brain Tumor MRI Data Mask R CNN Image Difference

March 10, 2022

Deep Convolutional Neural Networks for Molecular Subtyping of Gliomas Using Magnetic Resonance Imaging
Dong Wei, Yiming Li, Yinyan Wang, Tianyi Qian, Yefeng Zheng
Convolutional Neural Network Deep Convolutional Neural Network Magnetic Resonance Imaging Brain Tumor Radiomics Feature Molecular Subtypes Glioma Subtype Classification

January 16, 2022

Is it Possible to Predict MGMT Promoter Methylation from Brain Tumor MRI Scans using Deep Learning Models?
Numan Saeed, Shahad Hardan, Kudaibergen Abutalip, Mohammad Yaqub
Deep Learning Model Brain Tumor Glioblastoma Patient Brain Cancer

January 14, 2022

A New Deep Hybrid Boosted and Ensemble Learning-based Brain Tumor Analysis using MRI
Mirza Mumtaz Zahoor, Shahzad Ahmad Qureshi, Saddam Hussain Khan, Asifullah Khan
Magnetic Resonance Imaging Tumor Segmentation Brain Tumor Hybrid Deep Learning Two Stage Deep Learning

January 12, 2022

Detection of brain tumors using machine learning algorithms
Horacio Corral, Javier Melchor, Balam Sotelo, Jorge Vera
General Analysis Data Detection Practical Algorithm New Machine Machine Learning Algorithm Brain Tumor

January 11, 2022

Reciprocal Adversarial Learning for Brain Tumor Segmentation: A Solution to BraTS Challenge 2021 Segmentation Task
Himashi Peiris, Zhaolin Chen, Gary Egan, Mehrtash Harandi
Adversarial Learning Segmentation Task Solution Path Brain Tumor Segmentation Brain Tumor Robust Segmentation BRAT Challenge Virtual Adversarial Training Reciprocal Learning

January 4, 2022

Swin UNETR: Swin Transformers for Semantic Segmentation of Brain Tumors in MRI Images
Ali Hatamizadeh, Vishwesh Nath, Yucheng Tang, Dong Yang, Holger Roth, Daguang Xu
Convolutional Neural Network Semantic Segmentation Swin Transformer Brain Tumor Magnetic Resonance Image Medical Image Analysis Task Swin Unet TRansformer

December 28, 2021

Brain Tumor Classification by Cascaded Multiscale Multitask Learning Framework Based on Feature Aggregation
Zahra Sobhaninia, Nader Karimi, Pejman Khadivi, Shadrokh Samavi
Tumor Segmentation Brain Tumor Segmentation Brain Tumor Feature Aggregation Brain Tumor Classification

November 29, 2021

November 5, 2021

Segmentation of 2D Brain MR Images
Angad Ripudaman Singh Bajwa
Segmentation Based Approach Brain Tumor Segmentation Brain Tumor MRI Slice Medical Image Processing

August 12, 2020

Uncertainty Quantification using Variational Inference for Biomedical Image Segmentation
Abhinav Sagar
Deep Learning Convolutional Neural Network Uncertainty Quantification Variational Inference Image Segmentation Brain Tumor Biomedical Image Segmentation

Brain Tumor

Papers

Modeling of Textures to Predict Immune Cell Status and Survival of Brain Tumour Patients

Examining the behaviour of state-of-the-art convolutional neural networks for brain tumor detection with and without transfer learning

Preoperative brain tumor imaging: models and software for segmentation and standardized reporting

Brain Tumor Detection and Classification Using a New Evolutionary Convolutional Neural Network

A Novel Mask R-CNN Model to Segment Heterogeneous Brain Tumors through Image Subtraction

Deep Convolutional Neural Networks for Molecular Subtyping of Gliomas Using Magnetic Resonance Imaging

Is it Possible to Predict MGMT Promoter Methylation from Brain Tumor MRI Scans using Deep Learning Models?

A New Deep Hybrid Boosted and Ensemble Learning-based Brain Tumor Analysis using MRI

Detection of brain tumors using machine learning algorithms

Reciprocal Adversarial Learning for Brain Tumor Segmentation: A Solution to BraTS Challenge 2021 Segmentation Task

Swin UNETR: Swin Transformers for Semantic Segmentation of Brain Tumors in MRI Images

Brain Tumor Classification by Cascaded Multiscale Multitask Learning Framework Based on Feature Aggregation

Improving the Segmentation of Pediatric Low-Grade Gliomas through Multitask Learning

Data Augmentation For Medical MR Image Using Generative Adversarial Networks

Segmentation of 2D Brain MR Images

Uncertainty Quantification using Variational Inference for Biomedical Image Segmentation