Deep learning with radiomics for disease diagnosis and treatment: challenges and potential
The high-throughput extraction of quantitative imaging features from medical images for the
purpose of radiomic analysis, ie, radiomics in a broad sense, is a rapidly developing and …
purpose of radiomic analysis, ie, radiomics in a broad sense, is a rapidly developing and …
Predictive biomarkers of response to neoadjuvant chemotherapy in breast cancer: current and future perspectives for precision medicine
F Derouane, C van Marcke, M Berlière, A Gerday… - Cancers, 2022 - mdpi.com
Simple Summary Despite the increased use of neoadjuvant chemotherapy in the early
setting of breast cancer, there is a clinical need for predictive markers of response in daily …
setting of breast cancer, there is a clinical need for predictive markers of response in daily …
Radiomics and artificial intelligence in breast imaging: a survey
Medical imaging techniques, such as mammography, ultrasound and magnetic resonance
imaging, plays an integral role in the detection and characterization of breast cancer …
imaging, plays an integral role in the detection and characterization of breast cancer …
Deep learning radiomic analysis of DCE-MRI combined with clinical characteristics predicts pathological complete response to neoadjuvant chemotherapy in breast …
Objective The aim of this study was to develop and validate a deep learning-based radiomic
(DLR) model combined with clinical characteristics for predicting pathological complete …
(DLR) model combined with clinical characteristics for predicting pathological complete …
Ultrasound radiomics in personalized breast management: Current status and future prospects
J Gu, T Jiang - Frontiers in oncology, 2022 - frontiersin.org
Breast cancer is the most common cancer in women worldwide. Providing accurate and
efficient diagnosis, risk stratification and timely adjustment of treatment strategies are …
efficient diagnosis, risk stratification and timely adjustment of treatment strategies are …
Classification of metastatic lymph nodes in vivo using quantitative ultrasound at clinical frequencies
Quantitative ultrasound (QUS) methods characterizing the backscattered echo signal have
been of use in assessing tissue microstructure. High-frequency (30 MHz) QUS methods …
been of use in assessing tissue microstructure. High-frequency (30 MHz) QUS methods …
Artificial intelligence to support person-centred care in breast imaging-A scoping review
M Champendal, L Marmy, C Malamateniou… - Journal of medical …, 2023 - Elsevier
Abstract Aim To overview Artificial Intelligence (AI) developments and applications in breast
imaging (BI) focused on providing person-centred care in diagnosis and treatment for breast …
imaging (BI) focused on providing person-centred care in diagnosis and treatment for breast …
Disease-specific imaging utilizing support vector machine classification of H-scan parameters: assessment of steatosis in a rat model
In medical imaging, quantitative measurements have shown promise in identifying diseases
by classifying normal versus pathological parameters from tissues. The support vector …
by classifying normal versus pathological parameters from tissues. The support vector …
Multiparametric ultrasound imaging for early‐stage steatosis: Comparison with magnetic resonance imaging‐based proton density fat fraction
Background The prevalence of liver diseases, especially steatosis, requires a more
convenient and noninvasive tool for liver diagnosis, which can be a surrogate for the gold …
convenient and noninvasive tool for liver diagnosis, which can be a surrogate for the gold …
[HTML][HTML] Quantitative ultrasound radiomics using texture derivatives in prediction of treatment response to neo-adjuvant chemotherapy for locally advanced breast …
Background: To investigate quantitative ultrasound (QUS) based higher-order texture
derivatives in predicting the response to neoadjuvant chemotherapy (NAC) in patients with …
derivatives in predicting the response to neoadjuvant chemotherapy (NAC) in patients with …