Search Results for author: Bin Zheng

Found 12 papers, 0 papers with code

Transformers Improve Breast Cancer Diagnosis from Unregistered Multi-View Mammograms

no code implementations21 Jun 2022 Xuxin Chen, Ke Zhang, Neman Abdoli, Patrik W. Gilley, Ximin Wang, Hong Liu, Bin Zheng, Yuchen Qiu

For this purpose, we employ local Transformer blocks to separately learn patch relationships within four mammograms acquired from two-view (CC/MLO) of two-side (right/left) breasts.

Image Registration

Virtual Adversarial Training for Semi-supervised Breast Mass Classification

no code implementations25 Jan 2022 Xuxin Chen, Ximin Wang, Ke Zhang, Kar-Ming Fung, Theresa C. Thai, Kathleen Moore, Robert S. Mannel, Hong Liu, Bin Zheng, Yuchen Qiu

This study aims to develop a novel computer-aided diagnosis (CAD) scheme for mammographic breast mass classification using semi-supervised learning.

Classification

Recent advances and clinical applications of deep learning in medical image analysis

no code implementations27 May 2021 Xuxin Chen, Ximin Wang, Ke Zhang, Kar-Ming Fung, Theresa C. Thai, Kathleen Moore, Robert S. Mannel, Hong Liu, Bin Zheng, Yuchen Qiu

Deep learning has received extensive research interest in developing new medical image processing algorithms, and deep learning based models have been remarkably successful in a variety of medical imaging tasks to support disease detection and diagnosis.

Image Registration Lesion Classification

Phase Separation of Polyelectrolytes: The Effect of Charge Regulation

no code implementations5 Mar 2021 Bin Zheng, Yael Avni, David Andelman, Rudolf Podgornik

Complex coacervation, known as the liquid-liquid phase separation of solutions with oppositely charged polyelectrolytes, has attracted substantial interest in recent years.

Soft Condensed Matter Statistical Mechanics

Coarse-to-fine Airway Segmentation Using Multi information Fusion Network and CNN-based Region Growing

no code implementations25 Feb 2021 Jinquan Guo, Rongda Fu, Lin Pan, Shaohua Zheng, Liqin Huang, Bin Zheng, Bingwei He

To improve the performance of the segmentation result, the CNN-based region growing method is designed to focus on obtaining small branches.

Computed Tomography (CT) Segmentation

Interpretative Computer-aided Lung Cancer Diagnosis: from Radiology Analysis to Malignancy Evaluation

no code implementations22 Feb 2021 Shaohua Zheng, Zhiqiang Shen, Chenhao Peia, Wangbin Ding, Haojin Lin, Jiepeng Zheng, Lin Pan, Bin Zheng, Liqin Huang

In addition, explanations of CDAM features proved that the shape and density of nodule regions were two critical factors that influence a nodule to be inferred as malignant, which conforms with the diagnosis cognition of experienced radiologists.

Lung Cancer Diagnosis

Evaluation of company investment value based on machine learning

no code implementations30 Sep 2020 Junfeng Hu, Xiaosa Li, Yuru Xu, Shaowu Wu, Bin Zheng

In this paper, company investment value evaluation models are established based on comprehensive company information.

BIG-bench Machine Learning Dimensionality Reduction +2

SD-CNN: a Shallow-Deep CNN for Improved Breast Cancer Diagnosis

no code implementations1 Mar 2018 Fei Gao, Teresa Wu, Jing Li, Bin Zheng, Lingxiang Ruan, Desheng Shang, Bhavika Patel

To evaluate the validity of our approach, we first develop a deep-CNN using 49 CEDM cases collected from Mayo Clinic to prove the contributions from recombined images for improved breast cancer diagnosis (0. 86 in accuracy using LE imaging vs. 0. 90 in accuracy using both LE and recombined imaging).

Cannot find the paper you are looking for? You can Submit a new open access paper.