4.8 Editorial Material

Deep learning accelerates whole slide imaging for next-generation digital pathology applications

Related references

Note: Only part of the references are listed.
Article Optics

GANscan: continuous scanning microscopy using deep learning deblurring

Michael John Fanous et al.

Summary: This study develops an ultra-fast imaging method called GANscan, which continuously acquires data and restores sharp images from motion blurred videos. Compared to traditional stop-and-stare systems, this method has a 30x faster image acquisition speed and does not require specialized hardware.

LIGHT-SCIENCE & APPLICATIONS (2022)

Article Computer Science, Information Systems

Image-to-Image Translation: Methods and Applications

Yingxue Pang et al.

Summary: This paper provides an overview of recent developments in image-to-image translation (I2I), analyzing the key techniques and progress made in the field. It discusses the impact of I2I on research and industry, as well as the remaining challenges in related fields.

IEEE TRANSACTIONS ON MULTIMEDIA (2022)

Article Nanoscience & Nanotechnology

Single-Shot Autofocusing of Microscopy Images Using Deep Learning

Yilin Luo et al.

Summary: Autofocusing is critical for high-quality microscopic imaging, with hardware-based and algorithmic methods being the main approaches. The deep learning-based offline autofocusing method Deep-R is significantly faster than standard online algorithmic autofocusing methods, allowing for rapid and blind autofocusing of microscope images.

ACS PHOTONICS (2021)

Article Multidisciplinary Sciences

Deep learning-based transformation of H&E stained tissues into special stains

Kevin de Haan et al.

Summary: A method for digitally transforming H&E stained tissue into special stains was introduced, showing improved diagnosis over using H&E only. Computational stain transformation from H&E to special stains demonstrated utility in improving diagnoses of non-neoplastic kidney diseases, providing time and cost savings.

NATURE COMMUNICATIONS (2021)

Article Computer Science, Hardware & Architecture

Generative Adversarial Networks

Ian Goodfellow et al.

COMMUNICATIONS OF THE ACM (2020)

Review Medicine, General & Internal

Digital Pathology: Advantages, Limitations and Emerging Perspectives

Stephan W. Jahn et al.

JOURNAL OF CLINICAL MEDICINE (2020)

Article Medical Laboratory Technology

A Practical Guide to Whole Slide Imaging A White Paper From the Digital Pathology Association

Mark D. Zarella et al.

ARCHIVES OF PATHOLOGY & LABORATORY MEDICINE (2019)

Article Engineering, Biomedical

Virtual histological staining of unlabelled tissue-autofluorescence images via deep learning

Yair Rivenson et al.

NATURE BIOMEDICAL ENGINEERING (2019)

Article Optics

Deep learning microscopy

Yair Rivenson et al.

OPTICA (2017)

Proceedings Paper Computer Science, Artificial Intelligence

Image-to-Image Translation with Conditional Adversarial Networks

Phillip Isola et al.

30TH IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2017) (2017)

Article Optics

Synthetic aperture-based on-chip microscopy

Wei Luo et al.

LIGHT-SCIENCE & APPLICATIONS (2015)

Article Biochemical Research Methods

Multiplexed coded illumination for Fourier Ptychography with an LED array microscope

Lei Tian et al.

BIOMEDICAL OPTICS EXPRESS (2014)

Article Optics

Wide-field, high-resolution Fourier ptychographic microscopy

Guoan Zheng et al.

NATURE PHOTONICS (2013)

Article Physics, Applied

A phase retrieval algorithm for shifting illumination

JM Rodenburg et al.

APPLIED PHYSICS LETTERS (2004)