Convolutional autoencoder based model HistoCAE for segmentation of viable tumor regions in liver whole-slide images

Convolutional autoencoder based model HistoCAE for segmentation of viable tumor regions in liver whole-slide images

Abstract Liver cancer is one of the leading causes of cancer deaths in Asia and Africa. It is caused by the Hepatocellular carcinoma (HCC) in almost 90% of all cases. HCC is a malignant tumor and the most common histological type of the primary liver cancers. The detection and evaluation of viable t...

Full description

Bibliographic Details
Main Authors:	Mousumi Roy, Jun Kong, Satyananda Kashyap, Vito Paolo Pastore, Fusheng Wang, Ken C. L. Wong, Vandana Mukherjee
Format:	Article
Language:	English
Published:	Nature Portfolio 2021-01-01
Series:	Scientific Reports
Online Access:	https://doi.org/10.1038/s41598-020-80610-9

Similar Items

Histo-fetch – on-the-fly processing of gigapixel whole slide images simplifies and speeds neural network training
by: Brendon Lutnick, et al.
Published: (2022-01-01)

Histo-fetch – On-the-fly processing of gigapixel whole slide images simplifies and speeds neural network training
by: Brendon Lutnick, et al.
Published: (2022-01-01)

Unsupervised Anomaly Detection of Industrial Robots Using Sliding-Window Convolutional Variational Autoencoder
by: Tingting Chen, et al.
Published: (2020-01-01)

Deep learning based registration of serial whole-slide histopathology images in different stains
by: Mousumi Roy, et al.
Published: (2023-01-01)

HistoGuide mobile application (virtual microscopy and slides): A quantitative usability pilot study
by: Teoh Chern Zhong, et al.
Published: (2022-11-01)

HistoMIL: A Python package for training multiple instance learning models on histopathology slides
by: Shi Pan, et al.
Published: (2023-10-01)

CAE-COVIDX: automatic covid-19 disease detection based on x-ray images using enhanced deep convolutional and autoencoder
by: Hanafi Hanafi, et al.
Published: (2021-03-01)

Histo− and Dynamorphisms Revisited
by: Hinze, R, et al.
Published: (2013)

Viable and necrotic tumor assessment from whole slide images of osteosarcoma using machine-learning and deep-learning models.
by: Harish Babu Arunachalam, et al.
Published: (2019-01-01)

Graph autoencoder with mirror temporal convolutional networks for traffic anomaly detection
by: Zhiyu Ren, et al.
Published: (2024-01-01)

HistoEnder: A 3D printer-based histological slide autostainer that retains 3D printer functions
by: Marco Ponzetti, et al.
Published: (2022-10-01)

Convolutional Autoencoder-Based Multispectral Image Fusion
by: Arian Azarang, et al.
Published: (2019-01-01)

Resolution-agnostic tissue segmentation in whole-slide histopathology images with convolutional neural networks
by: Péter Bándi, et al.
Published: (2019-12-01)

Classification of melanocytic lesions in selected and whole-slide images via convolutional neural networks
by: Steven N Hart, et al.
Published: (2019-01-01)

Indoor Localization With an Autoencoder-Based Convolutional Neural Network
by: Hatice Arslantas, et al.
Published: (2024-01-01)

End-to-End Convolutional Autoencoder for Nonlinear Hyperspectral Unmixing
by: Mohamad Dhaini, et al.
Published: (2022-07-01)

Learning a Convolutional Autoencoder for Nighttime Image Dehazing
by: Mengyao Feng, et al.
Published: (2020-08-01)

Hyperspectral Data Compression Using Fully Convolutional Autoencoder
by: Riccardo La Grassa, et al.
Published: (2022-05-01)

Unsupervised Domain Adaptation via Stacked Convolutional Autoencoder
by: Yi Zhu, et al.
Published: (2022-12-01)

Multi-stage convolutional autoencoder network for hyperspectral unmixing
by: Yang Yu, et al.
Published: (2022-09-01)

AN EXPLAINABLE CONVOLUTIONAL AUTOENCODER MODEL FOR UNSUPERVISED CHANGE DETECTION
by: L. Bergamasco, et al.
Published: (2020-08-01)

Laser stripe image denoising using convolutional autoencoder
by: Zhuoqun Fang, et al.
Published: (2018-12-01)

HISTO-ARCHITECTURE OF THE SMALL INTESTINE OF GAROLE SHEEP
by: R. Malakar, et al.
Published: (2023-06-01)

Corrections to “Unsupervised Anomaly Detection of Industrial Robots Using Sliding-Window Convolutional Variational Autoencoder”
by: Tingting Chen, et al.
Published: (2020-01-01)

An efficient compression of ECG signals using deep convolutional autoencoders
by: Yildirim, Ozal, et al.
Published: (2018)

Improving Variational Graph Autoencoders With Multi-Order Graph Convolutions
by: Lining Yuan, et al.
Published: (2024-01-01)

Classification of tropical cyclone rain patterns using convolutional autoencoder
by: Dasol Kim, et al.
Published: (2024-01-01)

Phonocardiography Signals Compression with Deep Convolutional Autoencoder for Telecare Applications
by: Ying-Ren Chien, et al.
Published: (2020-08-01)

Convolutional Autoencoder-Based Flaw Detection for Steel Wire Ropes
by: Guoyong Zhang, et al.
Published: (2020-11-01)

On the Effectiveness of Convolutional Autoencoders on Image-Based Personalized Recommender Systems
by: Eva Blanco-Mallo, et al.
Published: (2020-08-01)

Deep Learning for High-Impedance Fault Detection: Convolutional Autoencoders
by: Khushwant Rai, et al.
Published: (2021-06-01)

Video Anomaly Detection Based on Convolutional Recurrent AutoEncoder
by: Bokun Wang, et al.
Published: (2022-06-01)

DOA Estimation Based on Convolutional Autoencoder in the Presence of Array Imperfections
by: Dah-Chung Chang, et al.
Published: (2023-02-01)

Deep convolutional autoencoders as generic feature extractors in seismological applications
by: Qingkai Kong, et al.
Published: (2021-12-01)

Tensor Decomposition-Inspired Convolutional Autoencoders for Hyperspectral Anomaly Detection
by: Bangyong Sun, et al.
Published: (2022-01-01)

1D-CONVOLUTIONAL AUTOENCODER BASED HYPERSPECTRAL DATA COMPRESSION
by: J. Kuester, et al.
Published: (2021-06-01)

Pansharpening based on convolutional autoencoder and multi-scale guided filter
by: Ahmad AL Smadi, et al.
Published: (2021-07-01)

Detection of Freezing of Gait Using Unsupervised Convolutional Denoising Autoencoder
by: Mohd Halim Mohd Noor, et al.
Published: (2021-01-01)

End-to-End Image Steganography Using Deep Convolutional Autoencoders
by: Nandhini Subramanian, et al.
Published: (2021-01-01)

Anomaly Detection in Videos Using Optical Flow and Convolutional Autoencoder
by: Elvan Duman, et al.
Published: (2019-01-01)