Diagnosis of breast cancer for modern mammography using artificial intelligence

ImageNet classification with deep convolutional neural networks

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Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries

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Densely Connected Convolutional Networks

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ImageNet Large Scale Visual Recognition Challenge

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Untitled work

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INbreast

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A curated mammography data set for use in computer-aided detection and diagnosis research

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Detecting and classifying lesions in mammograms with Deep Learning

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A review of computer-aided diagnosis of breast cancer: Toward the detection of subtle signs

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A deep learning approach for the analysis of masses in mammograms with minimal user intervention

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Artificial Intelligence for Mammography and Digital Breast Tomosynthesis: Current Concepts and Future Perspectives

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Improvement in Sensitivity of Screening Mammography with Computer-Aided Detection:A Multiinstitutional Trial

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Mammographic Image Analysis Society (MIAS) database v1.21

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Three-Class Mammogram Classification Based on Descriptive CNN Features

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Classification of Mammogram Images Using Multiscale all Convolutional Neural Network (MA-CNN)

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A statistical based feature extraction method for breast cancer diagnosis in digital mammogram using multiresolution representation

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Intellectual detection and validation of automated mammogram breast cancer images by multi-class SVM using deep learning classification

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Proceedings of the 9th international workshop on Digital Mammography

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Radiobiological Aspects of Intraoperative Radiotherapy (IORT) with Isotropic Low-Energy X Rays for Early-Stage Breast Cancer

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Automated Breast Mass Classification System Using Deep Learning and Ensemble Learning in Digital Mammogram

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Machine Learning Methods for Computer-Aided Breast Cancer Diagnosis Using Histopathology: A Narrative Review

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Segmentation of Masses on Mammograms Using Data Augmentation and Deep Learning

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Malignant and nonmalignant classification of breast lesions in mammograms using convolutional neural networks

Houby, E. M. F. E., & Yassin, N. I. R. (2021) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2021.102954 · Cited by 83 · see citing works

Dataset of breast mammography images with masses

Huang, M., & Lin, T. (2020) · Data in Brief · doi:10.1016/j.dib.2020.105928 · Cited by 76 · see citing works

Using deep learning for mammography classification

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Fundus image quality enhancement for blood vessel detection via a neural network using CLAHE and Wiener filter

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AI-enhanced breast imaging: Where are we and where are we heading?

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Mammographic image classification with deep fusion learning

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Medical imaging technique using curvelet transform and machine learning for the automated diagnosis of breast cancer from thermal image

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Applications of Artificial Intelligence in Breast Imaging

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Automatic Detection of Pectoral Muscle Region for Computer-Aided Diagnosis Using MIAS Mammograms

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Classification of Mammograms Using Texture and CNN Based Extracted Features

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Neighborhood Structural Similarity Mapping for the Classification of Masses in Mammograms

Rabidas, R., Midya, A., & Chakraborty, J. (2017) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2017.2715021 · Cited by 42 · see citing works

Automated diagnosis of breast cancer using parameter optimized kernel extreme learning machine

Mohanty, F., Rup, S., & Dash, B. (2020) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2020.102108 · Cited by 42 · see citing works

A Novel Algorithm for Breast Mass Classification in Digital Mammography Based on Feature Fusion

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Optimal breast tumor diagnosis using discrete wavelet transform and deep belief network based on improved sunflower optimization method

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A new algorithm of image segmentation using curve fitting based higher order polynomial smoothing

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Using Convolutional Neural Network with Cheat Sheet and Data Augmentation to Detect Breast Cancer in Mammograms

Ramadan, S. Z. (2020) · Computational and Mathematical Methods in Medicine · doi:10.1155/2020/9523404 · Cited by 32 · see citing works

Self-regulated multilayer perceptron neural network for breast cancer classification

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Radiogenomics of gastroenterological cancer: The dawn of personalized medicine with artificial intelligence‐based image analysis

Hoshino, I., & Yokota, H. (2021) · Annals of Gastroenterological Surgery · doi:10.1002/ags3.12437 · Cited by 19 · see citing works

Matching Tumour Candidate Points in Multiple Mammographic Views for Breast Cancer Detection

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Mapping human visual representations in space and time by neural networks

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Breast Skin Line Segmentation on Digital Mammogram using Fractal Approach

Don, S., & Min, D. (2016) · Indian Journal of Science and Technology · doi:10.17485/ijst/2016/v9i31/85420 · Cited by 6 · see citing works

Dataset of Breast mammography images with Masses

Lin, T.-Y. (2020) · Data Archiving and Networked Services (DANS) · doi:10.17632/x7bvzv6cvr · Cited by 5 · see citing works

Medical Image Data Augmentation: Techniques, Comparisons and Interpretations

Goceri, E. (2023) · Artificial Intelligence Review · doi:10.1007/s10462-023-10453-z · Cited by 459 · see citing works

Implementing convolutional neural network model for prediction in medical imaging

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Deep Convolution Neural Network for RBC Images

Jatothu, R., Sireesha, A., Kumar, R. G., & Joshi, K. K. (2022) · International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems (ICSES) · doi:10.1109/icses55317.2022.9914363 · Cited by 2 · see citing works

CNN-based Transfer Learning for Covid-19 Diagnosis

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Deep Convolutional Neural Networks

Zhou, D., & Ju, L. B. (2021) · Wiley Encyclopedia of Electrical and Electronics Engineering · doi:10.1002/047134608x.w8424 · Cited by 8 · see citing works

Leaf Features Extraction for Plant Classification using CNN

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