New frontiers: an update on computer-aided diagnosis for breast imaging in the age of artificial intelligence
OBJECTIVE. The purpose of this article is to compare traditional versus machine learning–
based computer-aided detection (CAD) platforms in breast imaging with a focus on …
based computer-aided detection (CAD) platforms in breast imaging with a focus on …
Applying artificial intelligence technology to assist with breast cancer diagnosis and prognosis prediction
Breast cancer remains the most diagnosed cancer in women. Advances in medical imaging
modalities and technologies have greatly aided in the early detection of breast cancer and …
modalities and technologies have greatly aided in the early detection of breast cancer and …
Is bigger always better? A controversial journey to the center of machine learning design, with uses and misuses of big data for predicting water meter failures
In this paper, we describe the design of a machine learning-based classifier, tailored to
predict whether a water meter will fail or need a replacement. Our initial attempt to train a …
predict whether a water meter will fail or need a replacement. Our initial attempt to train a …
Development and assessment of a new global mammographic image feature analysis scheme to predict likelihood of malignant cases
M Heidari, S Mirniaharikandehei, W Liu… - IEEE transactions on …, 2019 - ieeexplore.ieee.org
This study aims to develop and evaluate a new computer-aided diagnosis (CADx) scheme
based on analysis of global mammographic image features to predict likelihood of cases …
based on analysis of global mammographic image features to predict likelihood of cases …
Improving mammography lesion classification by optimal fusion of handcrafted and deep transfer learning features
Objective. Handcrafted radiomics features or deep learning model-generated automated
features are commonly used to develop computer-aided diagnosis schemes of medical …
features are commonly used to develop computer-aided diagnosis schemes of medical …
Developing a quantitative ultrasound image feature analysis scheme to assess tumor treatment efficacy using a mouse model
S Mirniaharikandehei, J VanOsdol, M Heidari… - Scientific reports, 2019 - nature.com
The aim of this study is to investigate the feasibility of identifying and applying quantitative
imaging features computed from ultrasound images of athymic nude mice to predict tumor …
imaging features computed from ultrasound images of athymic nude mice to predict tumor …
Developing global image feature analysis models to predict cancer risk and prognosis
In order to develop precision or personalized medicine, identifying new quantitative imaging
markers and building machine learning models to predict cancer risk and prognosis has …
markers and building machine learning models to predict cancer risk and prognosis has …
Multi-path synergic fusion deep neural network framework for breast mass classification using digital breast tomosynthesis
L Wang, C Zheng, W Chen, Q He, X Li… - Physics in Medicine …, 2020 - iopscience.iop.org
Objective. To develop and evaluate a multi-path synergic fusion (MSF) deep neural network
model for breast mass classification using digital breast tomosynthesis (DBT). Methods. We …
model for breast mass classification using digital breast tomosynthesis (DBT). Methods. We …
[PDF][PDF] Developing Novel Computer Aided Diagnosis Schemes for Improved Classification of Mammography Detected Masses
M Jones - 2023 - core.ac.uk
Breast cancer has the highest incident rate and second highest mortality rate among
cancers in women [97]. Routine mammographic screening is considered a widely used cost …
cancers in women [97]. Routine mammographic screening is considered a widely used cost …
Comparison of performance in breast lesions classification using radiomics and deep transfer learning: an assessment study
Radiomics and deep transfer learning have been attracting broad research interest in
developing and optimizing CAD schemes of medical images. However, these two …
developing and optimizing CAD schemes of medical images. However, these two …