Search
Search Results
-
Breast MRI Multi-tumor Segmentation Using 3D Region Growing
Breast tumor is one of the most prominent indicators for diagnosis of breast cancer. Magnetic Resonance Imaging (MRI) is a relevant imaging modality...
-
Contrastive Learning-Based Breast Tumor Segmentation in DCE-MRI
Precise and automated segmentation of tumors from breast dynamic contrast-enhanced magnetic resonance images (DCE-MRI) is crucial for obtaining...
-
Multifractal analysis of MRI. images from breast cancer patients
The present study aims to evaluate the effectiveness of the multifractal analysis in classifying benign and malignant tumor cells on MRI (Magnetic...
-
Breast lesion detection from MRI images using quasi-oppositional slime mould algorithm
In recent years cancer on breast in women has increased rapidly worldwide. Therefore, the automatic segmentation of breast Dynamic Contrast-Enhanced...
-
Multispectral 3D Masked Autoencoders for Anomaly Detection in Non-Contrast Enhanced Breast MRI
Mammography is commonly used as an imaging technique in breast cancer screening but comes with the disadvantage of a high overdiagnosis rate and low...
-
Morpho-contour exponential estimation algorithm for predicting breast tumor growth from MRI imagery
Breast tumor grows rapidly have an elevated risk of progressing to a metastatic state, leading to the spread of tumor tissues to other regions of the...
-
MoSID: Modality-Specific Information Disentanglement from Multi-parametric MRI for Breast Tumor Segmentation
Breast cancer is a major health issue, causing millions of deaths each year worldwide. Magnetic Resonance Imaging (MRI) is an effective tool for...
-
CNN-based Whole Breast Segmentation in Longitudinal High-risk MRI Study
Segmentation of breast MRI in a longitudinal high-risk cohort is challenging due to considerable variability in image quality and artefacts, imaging...
-
SimPLe: Similarity-Aware Propagation Learning for Weakly-Supervised Breast Cancer Segmentation in DCE-MRI
Breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) plays an important role in the screening and prognosis assessment of high-risk...
-
Automatic detection of breast cancer for mastectomy based on MRI images using Mask R-CNN and Detectron2 models
Breast tumor diagnosis has seen widespread use of computer-aided techniques. Machine learning techniques can benefit doctors in making diagnosis...
-
Diffusion Kinetic Model for Breast Cancer Segmentation in Incomplete DCE-MRI
Recent researches on cancer segmentation in dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) usually resort to the combination of...
-
Semi-supervised Breast Lesion Segmentation Using Local Cross Triplet Loss for Ultrafast Dynamic Contrast-Enhanced MRI
Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and its fast variant, ultrafast DCE-MRI, are useful for the management of breast...
-
Joint model- and immunohistochemistry-driven few-shot learning scheme for breast cancer segmentation on 4D DCE-MRI
Automatic segmentation of breast cancer on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), which reveals both temporal and spatial...
-
Breast Cancer Detection Through Semantic Segmentation of MRI Images with DMFTNet
One in every six fatalities worldwide is due to cancer, which is the second leading cause of death. Women are more likely than men to develop breast...
-
Customized Position with a Breast Pad for MDCT – A Single-Institution Experience for Breast Cancer Staging
Precise breast cancer (BC) staging, according to TNM classification, is essential for the adequate treatment of every patient. Magnetic Resonance...
-
Generative Adversarial Networks for Domain Translation in Unpaired Breast DCE-MRI Datasets
Generative Adversarial Networks (GAN) are more and more gaining attention in the computer vision domain thanks to their ability to generate synthetic...
-
ML-Based Radiomics Analysis for Breast Cancer Classification in DCE-MRI
Breast cancer is the most common malignancy that threatening women’s health. Although Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI)...
-
Synthesis of Contrast-Enhanced Breast MRI Using T1- and Multi-b-Value DWI-Based Hierarchical Fusion Network with Attention Mechanism
Magnetic resonance imaging (MRI) is the most sensitive technique for breast cancer detection among current clinical imaging modalities....
-
Segmentation of breast lesion in DCE-MRI by multi-level thresholding using sine cosine algorithm with quasi opposition-based learning
In recent times, the high prevalence of breast cancer in women has increased significantly. Breast cancer diagnosis and detection employing...
-
Application of Active Learning-based on Uncertainty Quantification to Breast Segmentation in MRI
In medical image segmentation with deep learning, large amounts of annotated data are needed to train precise models. Such annotations are...