Top Papers: KI in der Krebserkennung (2017)

A survey on deep learning in medical image analysis

Geert Litjens, Thijs Kooi, Babak Ehteshami Bejnordi et al.

Medical Image Analysis

Dermatologist-level classification of skin cancer with deep neural networks

Andre Esteva, Brett Kuprel, Roberto A. Novoa et al.

Nature

QuPath: Open source software for digital pathology image analysis

Peter Bankhead, Maurice B. Loughrey, José A. Fernández et al.

Scientific Reports

ImageJ2: ImageJ for the next generation of scientific image data

Curtis Rueden, Johannes Schindelin, Mark Hiner et al.

BMC Bioinformatics

Deep Learning in Medical Image Analysis

Dinggang Shen, Guorong Wu, Heung‐Il Suk

Annual Review of Biomedical Engineering

Diagnostic Assessment of Deep Learning Algorithms for Detection of Lymph Node Metastases in Women With Breast Cancer

Babak Ehteshami Bejnordi, Mitko Veta, Paul Johannes van Diest et al.

JAMA

beta-VAE: Learning Basic Visual Concepts with a Constrained Variational Framework

Irina Higgins, Löıc Matthey, Arka Pal et al.

International Conference on Learning Representations

Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour

Priya Goyal, Piotr Dollár, Ross Girshick et al.

arXiv (Cornell University)

Machine Learning for Medical Imaging

Bradley J. Erickson, Panagiotis Korfiatis, Zeynettin Akkus et al.

Radiographics

Deep Learning Applications in Medical Image Analysis

Justin Ker, Lipo Wang, Jai Prashanth Rao et al.

IEEE Access

Deep Learning in Medical Imaging: General Overview

June‐Goo Lee, Sanghoon Jun, Young-Won Cho et al.

Korean Journal of Radiology

Deep Learning for Medical Image Processing: Overview, Challenges and the Future

Imran Razzak, Saeeda Naz, Ahmad Zaib

Lecture notes in computational vision and biomechanics

Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support

M. Jorge Cardoso, Tal Arbel, Gustavo Carneiro et al.

Lecture notes in computer science

A Dataset and a Technique for Generalized Nuclear Segmentation for Computational Pathology

Neeraj Kumar, Ruchika Verma, Sanuj Sharma et al.

IEEE Transactions on Medical Imaging

Deep Learning: A Primer for Radiologists

Gabriel Chartrand, Phillip M. Cheng, Eugene Vorontsov et al.

Radiographics

Overview of deep learning in medical imaging

Kenji Suzuki

Radiological Physics and Technology

Classification using deep learning neural networks for brain tumors

Heba Mohsen, El‐Sayed A. El‐Dahshan, El-Sayed M. El-Horbaty et al.

Future Computing and Informatics Journal

Classification of breast cancer histology images using Convolutional Neural Networks

Teresa Araújo, Guilherme Aresta, Eduardo Castro et al.

PLoS ONE

Automated Breast Ultrasound Lesions Detection Using Convolutional Neural Networks

Moi Hoon Yap, Gérard Pons, Robert Martí et al.

IEEE Journal of Biomedical and Health Informatics

QuPath: Open source software for digital pathology image analysis

Peter Bankhead, Maurice B. Loughrey, José A. Fernández et al.

bioRxiv (Cold Spring Harbor Laboratory)

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

Rebecca Sawyer Lee, Francisco Javier Giménez Fuentes‐Guerra, Assaf Hoogi et al.

Scientific Data

Automatic Skin Lesion Segmentation Using Deep Fully Convolutional Networks With Jaccard Distance

Yading Yuan, Ming Chao, Yeh‐Chi Lo

IEEE Transactions on Medical Imaging

Breast Cancer Multi-classification from Histopathological Images with Structured Deep Learning Model

Zhongyi Han, Benzheng Wei, Yuanjie Zheng et al.

Scientific Reports

Radiomics strategies for risk assessment of tumour failure in head-and-neck cancer

Martin Vallières, Emily Kay‐Rivest, Léo Jean Perrin et al.

Scientific Reports

Accurate and reproducible invasive breast cancer detection in whole-slide images: A Deep Learning approach for quantifying tumor extent

Ángel Cruz-Roa, Hannah Gilmore, Ajay Basavanhally et al.

Scientific Reports

Detecting Cancer Metastases on Gigapixel Pathology Images

Yun Liu, Krishna Gadepalli, Mohammad Norouzi et al.

arXiv (Cornell University)

Beyond imaging: The promise of radiomics

Michele Avanzo, Joseph Stancanello, Issam El Naqa

Physica Medica

BI-RADS ® fifth edition: A summary of changes

David Spak, Jeri Sue Plaxco, Lumarie Santiago et al.

Diagnostic and Interventional Imaging

Deep Learning in Microscopy Image Analysis: A Survey

Fuyong Xing, Yuanpu Xie, Hai Su et al.

IEEE Transactions on Neural Networks and Learning Systems

Multimodal Neuroimaging Feature Learning With Multimodal Stacked Deep Polynomial Networks for Diagnosis of Alzheimer's Disease

Jun Shi, Zheng Xiao, Yan Li et al.

IEEE Journal of Biomedical and Health Informatics

Medical image retrieval using deep convolutional neural network

Adnan Qayyum, Syed Muhammad Anwar, Muhammad Awais et al.

Neurocomputing

Deep Feature Learning for Medical Image Analysis with Convolutional Autoencoder Neural Network

Min Chen, Xiaobo Shi, Yin Zhang⋆ et al.

IEEE Transactions on Big Data

A support vector machine-based ensemble algorithm for breast cancer diagnosis

Haifeng Wang, Bichen Zheng, Sang Won Yoon et al.

European Journal of Operational Research

End-to-End Adversarial Retinal Image Synthesis

Pedro Costa, Adrián Galdrán, Maria Inês Meyer et al.

IEEE Transactions on Medical Imaging

Large scale tissue histopathology image classification, segmentation, and visualization via deep convolutional activation features

Yan Xu, Zhipeng Jia, Liang-Bo Wang et al.

BMC Bioinformatics

Using Deep Learning for Classification of Lung Nodules on Computed Tomography Images

Qingzeng Song, Lei Zhao, XingKe Luo et al.

Journal of Healthcare Engineering

Radiomics in Brain Tumor: Image Assessment, Quantitative Feature Descriptors, and Machine-Learning Approaches

Mu Zhou, Jacob G. Scott, Baishali Chaudhury et al.

American Journal of Neuroradiology

Residual and plain convolutional neural networks for 3D brain MRI classification

Sergey Korolev, Amir Safiullin, Mikhail Belyaev et al.

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Pathologists’ diagnosis of invasive melanoma and melanocytic proliferations: observer accuracy and reproducibility study

Joann G. Elmore, Raymond L. Barnhill, David E. Elder et al.

BMJ

DeepPap: Deep Convolutional Networks for Cervical Cell Classification

Ling Zhang, Le Lu, Isabella Nogues et al.

IEEE Journal of Biomedical and Health Informatics

Deep Adversarial Networks for Biomedical Image Segmentation Utilizing Unannotated Images

Yizhe Zhang, Lin Yang, Jianxu Chen et al.

Lecture notes in computer science

AfterQC: automatic filtering, trimming, error removing and quality control for fastq data

Shifu Chen, Tanxiao Huang, Yanqing Zhou et al.

BMC Bioinformatics

A deep feature fusion methodology for breast cancer diagnosis demonstrated on three imaging modality datasets

Hui Li, Benjamin Q. Huynh, Maryellen L. Giger

Medical Physics

Machine learning techniques for breast cancer computer aided diagnosis using different image modalities: A systematic review

Nisreen I. R. Yassin, Shaimaa Omran, Enas M. F. El Houby et al.

Computer Methods and Programs in Biomedicine

Thyroid Nodule Classification in Ultrasound Images by Fine-Tuning Deep Convolutional Neural Network

Jianning Chi, Ekta Walia, Paul Babyn et al.

Journal of Digital Imaging

Whole Slide Imaging Versus Microscopy for Primary Diagnosis in Surgical Pathology

Sanjay Mukhopadhyay, Michael D. Feldman, Esther Abels et al.

The American Journal of Surgical Pathology

A deep learning framework for supporting the classification of breast lesions in ultrasound images

Seokmin Han, Ho-Kyung Kang, Ja-Yeon Jeong et al.

Physics in Medicine and Biology

Deep Learning for Classification of Colorectal Polyps on Whole-slide Images

Bruno Korbar, Andrea M. Olofson, Allen P. Miraflor et al.

Journal of Pathology Informatics

Skin Lesion Classification from Dermoscopic Images Using Deep Learning Techniques

Adrià Romero-López, Xavier Giró-i-Nieto, Jack Burdick et al.

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Deep Learning in Mammography

Anton S. Becker, Magda Marcon, Soleen Ghafoor et al.

Investigative Radiology