J
Jingxin Liu
Researcher at Shenzhen University
Publications - 33
Citations - 385
Jingxin Liu is an academic researcher from Shenzhen University. The author has contributed to research in topics: Deep learning & Segmentation. The author has an hindex of 7, co-authored 28 publications receiving 127 citations. Previous affiliations of Jingxin Liu include Fudan University & The University of Nottingham Ningbo China.
Papers
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Journal ArticleDOI
Attention by Selection: A Deep Selective Attention Approach to Breast Cancer Classification
Bolei Xu,Jingxin Liu,Xianxu Hou,Bozhi Liu,Jon Garibaldi,Ian O. Ellis,Andrew R. Green,Linlin Shen,Guoping Qiu +8 more
TL;DR: This work proposes a deep selective attention approach that aims to select valuable regions in the original images for classification, and demonstrates superior performance compared to state-of-the-art deep learning approaches.
Journal ArticleDOI
Mitosis domain generalization in histopathology images - The MIDOG challenge
Marc Aubreville,N. Stathonikos,Christof A. Bertram,Robert Klopleisch,Natalie D. ter Hoeve,Francesco Ciompi,Frauke Wilm,Christian Marzahl,Tim Donovan,Andreas Maier,Jack Breen,Nishant Ravikumar,You Lun. Chung,Jinah Park,Ramin Nateghi,Fattaneh Pourakpour,Rutger Fick,Saima Ben Hadj,Mostafa Jahanifar,Nasir M. Rajpoot,Jakob Dexl,Thomas Wittenberg,Satoshi Kondo,Maxime W. Lafarge,Viktor H. Koelzer,Yubo Wang,Xing-An Long,Jingxin Liu,Salar Razavi,April Khademi,Sen Yang,Xiyue Wang,Mitko Veta,Katharina Breininger +33 more
TL;DR: The MICCAI MIDOG 2021 challenge as mentioned in this paper was the first attempt to derive scanner-agnostic mitosis detection algorithms, which used a training set of 200 cases, split across four scanning systems.
Journal ArticleDOI
An End-to-End Deep Learning Histochemical Scoring System for Breast Cancer TMA
Jingxin Liu,Bolei Xu,Chi Zheng,Yuanhao Gong,Jon Garibaldi,Daniele Soria,Andew Green,Ian O. Ellis,Wenbin Zou,Guoping Qiu +9 more
TL;DR: Experimental results are presented, which demonstrate that the H-Scores predicted by the model have very high and statistically significant correlation with experienced pathologists’ scores and that theH-Score discrepancy between the algorithm and the pathologists is on par with the inter-subject discrepancy betweenThe pathologists.
Journal ArticleDOI
Learning Based Image Transformation Using Convolutional Neural Networks
TL;DR: This is the first work that uses deep learning to solve and unify these three common image processing tasks: downscaling, decolorization, and high dynamic range image tone mapping.
Journal ArticleDOI
GCSBA-Net: Gabor-Based and Cascade Squeeze Bi-Attention Network for Gland Segmentation
TL;DR: A Gabor-based module is utilized to extract texture information at different scales and directions in histopathology images to solve the imbalance of data distribution and boundary blur and a hybrid loss function to response the object boudary better is proposed.