[HTML][HTML] Dataset of breast ultrasound images
Breast cancer is one of the most common causes of death among women worldwide. Early
detection helps in reducing the number of early deaths. The data presented in this article …
detection helps in reducing the number of early deaths. The data presented in this article …
Recent progress in transformer-based medical image analysis
The transformer is primarily used in the field of natural language processing. Recently, it has
been adopted and shows promise in the computer vision (CV) field. Medical image analysis …
been adopted and shows promise in the computer vision (CV) field. Medical image analysis …
Multi-task learning for segmentation and classification of tumors in 3D automated breast ultrasound images
Tumor classification and segmentation are two important tasks for computer-aided diagnosis
(CAD) using 3D automated breast ultrasound (ABUS) images. However, they are …
(CAD) using 3D automated breast ultrasound (ABUS) images. However, they are …
Artificial intelligence system reduces false-positive findings in the interpretation of breast ultrasound exams
Though consistently shown to detect mammographically occult cancers, breast ultrasound
has been noted to have high false-positive rates. In this work, we present an AI system that …
has been noted to have high false-positive rates. In this work, we present an AI system that …
Vision transformers for classification of breast ultrasound images
Medical ultrasound (US) imaging has become a prominent modality for breast cancer
imaging due to its ease of use, low cost, and safety. In the past decade, convolutional neural …
imaging due to its ease of use, low cost, and safety. In the past decade, convolutional neural …
[HTML][HTML] Breast mass segmentation in ultrasound with selective kernel U-Net convolutional neural network
M Byra, P Jarosik, A Szubert, M Galperin… - … Signal Processing and …, 2020 - Elsevier
In this work, we propose a deep learning method for breast mass segmentation in
ultrasound (US). Variations in breast mass size and image characteristics make the …
ultrasound (US). Variations in breast mass size and image characteristics make the …
Classification of benign and malignant subtypes of breast cancer histopathology imaging using hybrid CNN-LSTM based transfer learning
MM Srikantamurthy, VPS Rallabandi, DB Dudekula… - BMC Medical …, 2023 - Springer
Background Grading of cancer histopathology slides requires more pathologists and expert
clinicians as well as it is time consuming to look manually into whole-slide images. Hence …
clinicians as well as it is time consuming to look manually into whole-slide images. Hence …
High accuracy hybrid CNN classifiers for breast cancer detection using mammogram and ultrasound datasets
Breast cancer is a significant cause of cancer fatality among women all over the world.
Hence the detection of this disease at the initial stage works as a boon to the patient so that …
Hence the detection of this disease at the initial stage works as a boon to the patient so that …
Automated diagnosis of breast cancer using multi-modal datasets: A deep convolution neural network based approach
This paper proposes a deep convolutional neural network (CNN) model for automated
breast cancer classification from a different class of images, namely, mammograms and …
breast cancer classification from a different class of images, namely, mammograms and …
A yolo-based model for breast cancer detection in mammograms
This work aims to implement an automated data-driven model for breast cancer detection in
mammograms to support physicians' decision process within a breast cancer screening or …
mammograms to support physicians' decision process within a breast cancer screening or …