[HTML][HTML] Deep learning in different ultrasound methods for breast cancer, from diagnosis to prognosis: current trends, challenges, and an analysis

H Afrin, NB Larson, M Fatemi, A Alizad - Cancers, 2023 - mdpi.com
Simple Summary Breast cancer is one of the leading causes of cancer death among women.
Ultrasound is a harmless imaging modality used to help make decisions about who should …

A review on computational methods for breast cancer detection in ultrasound images using multi-image modalities

S Sushanki, AK Bhandari, AK Singh - Archives of Computational Methods …, 2024 - Springer
Breast cancer is a kind of cancer that develops and propagates from tissues of the breast
and slowly transcends the whole body, this type of tumor is found in both sexes. Early …

Breast Cancer Classification from Mammogram Images Using Extreme Learning Machine‐Based DenseNet121 Model

RK Pattanaik, S Mishra, M Siddique… - Journal of …, 2022 - Wiley Online Library
Breast cancer is characterized by abnormal discontinuities in the lining cells of a woman's
milk duct. Large numbers of women die from breast cancer as a result of developing …

MRI based radiomics approach with deep learning for prediction of vessel invasion in early-stage cervical cancer

X Jiang, J Li, Y Kan, T Yu, S Chang… - … ACM transactions on …, 2020 - ieeexplore.ieee.org
This article aims to build deep learning-based radiomic methods in differentiating vessel
invasion from non-vessel invasion in cervical cancer with multi-parametric MRI data. A set of …

Meningiomas: Preoperative predictive histopathological grading based on radiomics of MRI

Y Han, T Wang, P Wu, H Zhang, H Chen… - Magnetic Resonance …, 2021 - Elsevier
Purpose We aimed to develop a radiomics model to predict the histopathological grading of
meningiomas by magnetic resonance imaging (MRI) before surgery. Methods We recruited …

[HTML][HTML] Radiomics model for distinguishing tuberculosis and lung cancer on computed tomography scans

EN Cui, T Yu, SJ Shang, XY Wang, YL Jin… - World journal of …, 2020 - ncbi.nlm.nih.gov
BACKGROUND Pulmonary tuberculosis (TB) and lung cancer (LC) are common diseases
with a high incidence and similar symptoms, which may be misdiagnosed by radiologists …

Multiparametric MRI‐based radiomics approaches for preoperative prediction of EGFR mutation status in spinal bone metastases in patients with lung …

X Jiang, M Ren, X Shuang, H Yang… - Journal of Magnetic …, 2021 - Wiley Online Library
Background Preoperative prediction of epidermal growth factor receptor (EGFR) mutation
status in patients with spinal bone metastases (SBM) from primary lung adenocarcinoma is …

A multi-organ cancer study of the classification performance using 2D and 3D image features in radiomics analysis

L Xu, P Yang, EA Yen, Y Wan, Y Jiang… - Physics in Medicine …, 2019 - iopscience.iop.org
A multi-organ cancer study of the classification performance using 2D and 3D image features
in radiomics analysis - IOPscience This site uses cookies. By continuing to use this site you …

Lymph-vascular space invasion prediction in cervical cancer: exploring radiomics and deep learning multilevel features of tumor and peritumor tissue on …

W Hua, T Xiao, X Jiang, Z Liu, M Wang, H Zheng… - … Signal Processing and …, 2020 - Elsevier
Preoperative determination of the presence of LVSI plays an important role in guiding
surgical planning. In this paper, multiparametric magnetic resonance imaging (MRI)-based …

Diagnosis and grading of vesicoureteral reflux on voiding cystourethrography images in children using a deep hybrid model

Y Eroglu, K Yildirim, A Çinar, M Yildirim - Computer Methods and Programs …, 2021 - Elsevier
Background and objective Vesicoureteral reflux is the leakage of urine from the bladder into
the ureter. As a result, urinary tract infections and kidney scarring can occur in children …