Detecting Cancerous Regions in DCE MRI using Functional Data, XGboost and Neural Networks

QR Code

Detecting Cancerous Regions in DCE MRI using Functional Data, XGboost and Neural Networks

Saved in:

Bibliographic Details
Main Authors:	Povilas Treigys, Aleksas Vaitulevičius, Jolita Bernatavičienė, Jurgita Markevičiūtė, Ieva Naruševičiūtė, Mantas Trakymas
Format:	Article
Language:	English
Published:	Polish Information Processing Society 2022-09-01
Series:	Annals of computer science and information systems
Online Access:	https://annals-csis.org/Volume_32/drp/pdf/128.pdf
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Deep Neural Networks application for Cup-to-Disc ratio estimation in eye fundus images
by: Sandra Virbukaitė, et al.
Published: (2023-09-01)

Assessment of tumor treatment response using active contrast encoding (ACE)-MRI: Comparison with conventional DCE-MRI.
by: Jin Zhang, et al.
Published: (2020-01-01)

Value of DCE-MRI parameters for short-term prognosis of pharyngeal cancer after postoperative radiotherapy
by: SUN Shengjie, et al.
Published: (2025-06-01)

Quantitative Classification of Uterine Myoma Perfusion on DCE-MRI: Retrospective Analysis of Data and Clinical Implications
by: Alan Bruszewski, et al.
Published: (2025-06-01)

Heterogeneity Assessment of Breast Cancer Tumor Microenvironment: Multiparametric Quantitative Analysis with DCE-MRI and Discovery of Radiomics Biomarkers
by: Ma W, et al.
Published: (2025-07-01)

Predicting the Costs of Forwarding Contracts Using XGBoost and a Deep Neural Network
by: Łukasz Podlodowski, et al.
Published: (2022-09-01)

Machine learning-based integration of DCE-MRI radiomics for STAT3 expression prediction and survival stratification in breast cancer
by: Dong Pan, et al.
Published: (2025-06-01)

Construction of VAE-GRU-XGBoost intrusion detection model for network security.
by: Yu Chen, et al.
Published: (2025-01-01)

Comparison of classical, xgboost and neural network methods for parameter estimation in epidemic processes on random graphs
by: Ágnes Backhausz, et al.
Published: (2025-06-01)

Optimizing Deep Learning Models for Luminal and Nonluminal Breast Cancer Classification Using Multidimensional ROI in DCE‐MRI—A Multicenter Study
by: Zhenfeng Huang, et al.
Published: (2025-05-01)

Diagnostic Performance of DCE-MRI Breast Using Kaiser Score in Characterization of Mass and Nonmass Lesions and Its Comparison with ACR BI-RADS
by: Prerna Garg, et al.

Intratumoral and Peritumoral Radiomics Based on DCE-MRI for Prediction of Microvascular Invasion Grading in Solitary Hepatocellular Carcinoma (&le;3 cm)
by: Li Y, et al.
Published: (2025-05-01)

The Forecast of the Wind Turbine Generated Power Using Hybrid (LTC + XGBoost) Model
by: Justina Krevnevičiūtė, et al.
Published: (2025-07-01)

Analytical Model of Crack Opening in Reinforced Concrete Structures Based on DCE
by: Vladimir I. Kolchunov, et al.
Published: (2025-06-01)

Radiomics and Machine Learning Approaches for the Preoperative Classification of In Situ vs. Invasive Breast Cancer Using Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE–MRI)
by: Luana Conte, et al.
Published: (2025-07-01)

Optimizing Tumor Detection in Brain MRI with One-Class SVM and Convolutional Neural Network-Based Feature Extraction
by: Azeddine Mjahad, et al.
Published: (2025-06-01)

UAV detection using neural networks
by: Maria D. Averina, et al.
Published: (2024-06-01)

Detection of Arrhythmia using Neural Network
by: Saumendra Kumar Mohapatra, et al.
Published: (2017-09-01)

Continuous Learning for Automated Early-Stage Alzheimer’s Detection Using MRI and Spike Neural Signals
by: Salar Jamal Abdulhameed Al-Atroshi, et al.
Published: (2025-01-01)

Enhancing Medicare Fraud Detection With a CNN-Transformer-XGBoost Framework and Explainable AI
by: Mohammad Balayet Hossain Sakil, et al.
Published: (2025-01-01)

Efficient slice anomaly detection network for 3D brain MRI Volume.
by: Zeduo Zhang, et al.
Published: (2025-06-01)

Voice Detection Using Convolutional Neural Network
by: U. A. Vishniakou, et al.
Published: (2023-04-01)

Series Arc Fault Detection Based on Improved Artificial Hummingbird Algorithm Optimizer Optimized XGBoost
by: Lichun Qi, et al.
Published: (2025-06-01)

Damage Resistance of an fMRI-Spiking Neural Network Based on Speech Recognition Against Stochastic Attack
by: Lei Guo, et al.
Published: (2025-06-01)

Simulated Annealing-Based Hyperparameter Optimization of a Convolutional Neural Network for MRI Brain Tumor Classification
by: Sofia El Amoury, et al.
Published: (2025-05-01)

Bone Segmentation in Low-Field Knee MRI Using a Three-Dimensional Convolutional Neural Network
by: Ciro Listone, et al.
Published: (2025-05-01)

Advancing brain tumor diagnosis: Deep siamese convolutional neural network as a superior model for MRI classification
by: Gowtham Murugesan, et al.
Published: (2025-06-01)

Resilience of Neural Networks Underlying the Stroop Effect in the Aftermath of Severe COVID-19: fMRI Pilot Study
by: Valérie Beaud, et al.
Published: (2025-06-01)

EDHD-FG-XGBoost: Entropy-driven high-dimensional feature gain XGBoost model for short-term wind power prediction and application
by: Xing Liu, et al.
Published: (2025-06-01)

Automatic detection of sleep spindles by neural networks algorithms
by: Jan Rychlík, et al.
Published: (2024-12-01)

Leveraging Graph Neural Networks for IoT Attack Detection
by: Mevlüt Uysal, et al.
Published: (2025-06-01)

An Improved DoH Traffic Classification Method for XGboost
by: LI Bo, et al.
Published: (2023-02-01)

Simulation of automatic intrusion detection in university networks by using neural network algorithms
by: Houdun Xu
Published: (2025-09-01)

Precise identification of medulloblastoma in MRI images using a convolutional neural network integrated with a self-attention mechanism
by: Chenhao Fang, et al.
Published: (2025-07-01)

BP Neural Network Fuse with Morphology Edge Detection Method
by: YUE Xin-hua, et al.
Published: (2021-10-01)

Anomaly Detection Approach Based on Deep Neural Network and Dropout
by: Zaid Hussien et al.
Published: (2020-06-01)

Explainable Graph Neural Networks for Power Grid Fault Detection
by: Richard Bosso, et al.
Published: (2025-01-01)

Application of Artificial Neural Networks for Defect Detection in Ceramic Materials
by: Tahir Cetin AKINCI, et al.
Published: (2013-10-01)

Detection of the Presence of Rail Corrugation Using Convolutional Neural Network
by: Maciej TABASZEWSKI, et al.
Published: (2022-12-01)

Systematic Review of Graph Neural Network for Malicious Attack Detection
by: Sarah Mohammed Alshehri, et al.
Published: (2025-06-01)