Recent advancements in artificial intelligence for breast cancer: Image augmentation, segmentation, diagnosis, and prognosis approaches
Breast cancer is a significant global health burden, with increasing morbidity and mortality
worldwide. Early screening and accurate diagnosis are crucial for improving prognosis …
worldwide. Early screening and accurate diagnosis are crucial for improving prognosis …
Information bottleneck-based interpretable multitask network for breast cancer classification and segmentation
Breast cancer is one of the most common causes of death among women worldwide. Early
signs of breast cancer can be an abnormality depicted on breast images (eg, mammography …
signs of breast cancer can be an abnormality depicted on breast images (eg, mammography …
A regional-attentive multi-task learning framework for breast ultrasound image segmentation and classification
Breast ultrasound (BUS) imaging is commonly used in the early detection of breast cancer
as a portable, valuable, and widely available diagnosis tool. Automated BUS image …
as a portable, valuable, and widely available diagnosis tool. Automated BUS image …
Joint localization and classification of breast masses on ultrasound images using an auxiliary attention-based framework
Multi-task learning (MTL) methods have been extensively employed for joint localization and
classification of breast lesions on ultrasound images to assist in cancer diagnosis and …
classification of breast lesions on ultrasound images to assist in cancer diagnosis and …
[HTML][HTML] Multi-Task Learning of Scanning Electron Microscopy and Synthetic Thermal Tomography Images for Detection of Defects in Additively Manufactured Metals
One of the key challenges in laser powder bed fusion (LPBF) additive manufacturing of
metals is the appearance of microscopic pores in 3D-printed metallic structures. Quality …
metals is the appearance of microscopic pores in 3D-printed metallic structures. Quality …
Breast ultrasound tumor classification using a hybrid multitask CNN-transformer network
Capturing global contextual information plays a critical role in breast ultrasound (BUS)
image classification. Although convolutional neural networks (CNNs) have demonstrated …
image classification. Although convolutional neural networks (CNNs) have demonstrated …
SaTransformer: Semantic‐aware transformer for breast cancer classification and segmentation
J Zhang, Z Zhang, H Liu, S Xu - IET Image Processing, 2023 - Wiley Online Library
Breast cancer classification and segmentation play an important role in identifying and
detecting benign and malignant breast lesions. However, segmentation and classification …
detecting benign and malignant breast lesions. However, segmentation and classification …
Nucleus segmentation and classification using residual SE-UNet and feature concatenation approach incervical cytopathology cell images
GJ Chowdary, P Yogarajah - Technology in Cancer …, 2023 - journals.sagepub.com
Introduction: Pap smear is considered to be the primary examination for the diagnosis of
cervical cancer. But the analysis of pap smear slides is a time-consuming task and tedious …
cervical cancer. But the analysis of pap smear slides is a time-consuming task and tedious …
Breast cancer classification and segmentation framework using multiscale CNN and U‐shaped dual decoded attention network
Breast cancer is a mostly diagnosed deadly disease with a high mortality rate that can
effectively be cured by early diagnosis and proper treatment. Ultrasound imaging modality is …
effectively be cured by early diagnosis and proper treatment. Ultrasound imaging modality is …
MsGoF: Breast lesion classification on ultrasound images by multi-scale gradational-order fusion framework
S Zhong, C Tu, X Dong, Q Feng, W Chen… - Computer Methods and …, 2023 - Elsevier
Abstract Background and Objective: Predicting the malignant potential of breast lesions
based on breast ultrasound (BUS) images is a crucial component of computer-aided …
based on breast ultrasound (BUS) images is a crucial component of computer-aided …