AIMC Topic: Breast Neoplasms

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The Role of a Deep Learning-Based Computer-Aided Diagnosis System and Elastography in Reducing Unnecessary Breast Lesion Biopsies.

Clinical breast cancer Dec 23, 2022
OBJECTIVES: Ultrasound examination has inter-observer and intra-observer variability and a high false-positive rate. The aim of this study was to evaluate the value of the combined use of a deep learning-based computer-aided diagnosis (CAD) system an...
Ultrasonography, Mammary Elasticity Imaging Techniques Breast Neoplasms Deep Learning Biopsy Female Sensitivity and Specificity Humans Computers Retrospective Studies
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Deep learning-based system for automatic prediction of triple-negative breast cancer from ultrasound images.

Medical & biological engineering & computing Dec 21, 2022
To develop a deep-learning system for the automatic identification of triple-negative breast cancer (TNBC) solely from ultrasound images. A total of 145 patients and 831 images were retrospectively enrolled at Peking Union College Hospital from April...
Female Breast Neoplasms Deep Learning Ultrasonography Triple Negative Breast Neoplasms Humans Retrospective Studies
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Predicting Underestimation of Invasive Cancer in Patients with Core-Needle-Biopsy-Diagnosed Ductal Carcinoma In Situ Using Deep Learning Algorithms.

Tomography (Ann Arbor, Mich.) Dec 20, 2022
The prediction of an occult invasive component in ductal carcinoma in situ (DCIS) before surgery is of clinical importance because the treatment strategies are different between pure DCIS without invasive component and upgraded DCIS. We demonstrated ...
Humans Neural Networks, Computer Algorithms Carcinoma, Intraductal, Noninfiltrating Female Breast Neoplasms Biopsy, Large-Core Needle Deep Learning
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Breast tumor localization and segmentation using machine learning techniques: Overview of datasets, findings, and methods.

Computers in biology and medicine Dec 19, 2022
The Global Cancer Statistics 2020 reported breast cancer (BC) as the most common diagnosis of cancer type. Therefore, early detection of such type of cancer would reduce the risk of death from it. Breast imaging techniques are one of the most frequen...
Mammary Neoplasms, Animal Image Processing, Computer-Assisted Mammography Machine Learning Female Breast Neoplasms Animals Humans Diagnosis, Computer-Assisted Deep Learning
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An open-access breast lesion ultrasound image database‏: Applicable in artificial intelligence studies.

Computers in biology and medicine Dec 16, 2022
Breast cancer is one of the largest single contributors to the burden of disease worldwide. Early detection of breast cancer has been shown to be associated with better overall clinical outcomes. Ultrasonography is a vital imaging modality in managin...
Databases, Factual Female Breast Neoplasms Humans Artificial Intelligence Diagnosis, Computer-Assisted Ultrasonography Ultrasonography, Mammary
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Attention-based deep learning for breast lesions classification on contrast enhanced spectral mammography: a multicentre study.

British journal of cancer Dec 15, 2022
BACKGROUND: This study aims to develop an attention-based deep learning model for distinguishing benign from malignant breast lesions on CESM.
Humans Neural Networks, Computer Female Deep Learning Mammography Sensitivity and Specificity Breast Breast Neoplasms
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Fully automatic tumor segmentation of breast ultrasound images with deep learning.

Journal of applied clinical medical physics Dec 9, 2022
BACKGROUND: Breast ultrasound (BUS) imaging is one of the most prevalent approaches for the detection of breast cancers. Tumor segmentation of BUS images can facilitate doctors in localizing tumors and is a necessary step for computer-aided diagnosis...
Image Processing, Computer-Assisted Humans Neural Networks, Computer Artificial Intelligence Female Breast Neoplasms Deep Learning
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Further predictive value of lymphovascular invasion explored via supervised deep learning for lymph node metastases in breast cancer.

Human pathology Dec 5, 2022
Lymphovascular invasion, specifically lymph-blood vessel invasion (LBVI), is a risk factor for metastases in breast invasive ductal carcinoma (IDC) and is routinely screened using hematoxylin-eosin histopathological images. However, routine reports o...
Prognosis Retrospective Studies Female Humans Lymphoma Breast Neoplasms Lymphatic Metastasis Deep Learning Breast Lymph Nodes
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Artificial intelligence assistance for women who had spot compression view: reducing recall rates for digital mammography.

Acta radiologica (Stockholm, Sweden : 1987) Nov 25, 2022
BACKGROUND: Mammography yields inevitable recall for indeterminate findings that need to be confirmed with additional views.
Retrospective Studies Early Detection of Cancer Humans Breast Mammography Female Breast Density Artificial Intelligence Breast Neoplasms
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Ultrasound-based deep learning in the establishment of a breast lesion risk stratification system: a multicenter study.

European radiology Nov 23, 2022
OBJECTIVES: To establish a breast lesion risk stratification system using ultrasound images to predict breast malignancy and assess Breast Imaging Reporting and Data System (BI-RADS) categories simultaneously.
Breast Neoplasms Risk Assessment Deep Learning Retrospective Studies Female Ultrasonography Humans Ultrasonography, Mammary Breast
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