b'Shunxing Bao'

research

∙ 09/05/2023

Evaluation Kidney Layer Segmentation on Whole Slide Imaging using Convolutional Neural Networks and Transformers

The segmentation of kidney layer structures, including cortex, outer str...

0 Muhao Liu, et al. ∙

research

∙ 08/20/2023

Cell Spatial Analysis in Crohn's Disease: Unveiling Local Cell Arrangement Pattern with Graph-based Signatures

Crohn's disease (CD) is a chronic and relapsing inflammatory condition t...

0 Shunxing Bao, et al. ∙

research

∙ 08/10/2023

Leverage Weakly Annotation to Pixel-wise Annotation via Zero-shot Segment Anything Model for Molecular-empowered Learning

Precise identification of multiple cell classes in high-resolution Giga-...

0 Xueyuan Li, et al. ∙

research

∙ 08/10/2023

High-performance Data Management for Whole Slide Image Analysis in Digital Pathology

When dealing with giga-pixel digital pathology in whole-slide imaging, a...

0 Haoju Leng, et al. ∙

research

∙ 08/10/2023

Multi-scale Multi-site Renal Microvascular Structures Segmentation for Whole Slide Imaging in Renal Pathology

Segmentation of microvascular structures, such as arterioles, venules, a...

0 Franklin Hu, et al. ∙

research

∙ 07/03/2023

Feasibility of Universal Anomaly Detection without Knowing the Abnormality in Medical Images

Many anomaly detection approaches, especially deep learning methods, hav...

0 Can Cui, et al. ∙

research

∙ 07/01/2023

All-in-SAM: from Weak Annotation to Pixel-wise Nuclei Segmentation with Prompt-based Finetuning

The Segment Anything Model (SAM) is a recently proposed prompt-based seg...

0 Can Cui, et al. ∙

research

∙ 04/24/2023

Exploring shared memory architectures for end-to-end gigapixel deep learning

Deep learning has made great strides in medical imaging, enabled by hard...

0 Lucas W. Remedios, et al. ∙

research

∙ 04/09/2023

Segment Anything Model (SAM) for Digital Pathology: Assess Zero-shot Segmentation on Whole Slide Imaging

The segment anything model (SAM) was released as a foundation model for ...

0 Ruining Deng, et al. ∙

research

∙ 04/01/2023

Cross-scale Multi-instance Learning for Pathological Image Diagnosis

Analyzing high resolution whole slide images (WSIs) with regard to infor...

8 Ruining Deng, et al. ∙

research

∙ 02/17/2023

DMSConfig: Automated Configuration Tuning for Distributed IoT Message Systems Using Deep Reinforcement Learning

The Distributed Messaging Systems (DMSs) used in IoT systems require tim...

0 Zhuangwei Kang, et al. ∙

research

∙ 09/29/2022

3D UX-Net: A Large Kernel Volumetric ConvNet Modernizing Hierarchical Transformer for Medical Image Segmentation

Vision transformers (ViTs) have quickly superseded convolutional network...

0 Ho Hin Lee, et al. ∙

research

∙ 08/30/2022

Compound Figure Separation of Biomedical Images: Mining Large Datasets for Self-supervised Learning

With the rapid development of self-supervised learning (e.g., contrastiv...

8 Tianyuan Yao, et al. ∙

research

∙ 08/15/2022

Cross-scale Attention Guided Multi-instance Learning for Crohn's Disease Diagnosis with Pathological Images

Multi-instance learning (MIL) is widely used in the computer-aided inter...

14 Ruining Deng, et al. ∙

research

∙ 05/12/2022

Pseudo-Label Guided Multi-Contrast Generalization for Non-Contrast Organ-Aware Segmentation

Non-contrast computed tomography (NCCT) is commonly acquired for lung ca...

4 Ho Hin Lee, et al. ∙

research

∙ 03/04/2022

Characterizing Renal Structures with 3D Block Aggregate Transformers

Efficiently quantifying renal structures can provide distinct spatial co...

4 Xin Yu, et al. ∙

research

∙ 09/18/2021

Random Multi-Channel Image Synthesis for Multiplexed Immunofluorescence Imaging

Multiplex immunofluorescence (MxIF) is an emerging imaging technique tha...

0 Shunxing Bao, et al. ∙

research

∙ 07/19/2021

Compound Figure Separation of Biomedical Images with Side Loss

Unsupervised learning algorithms (e.g., self-supervised learning, auto-e...

19 Tianyuan Yao, et al. ∙

research

∙ 06/03/2021

Attention-Guided Supervised Contrastive Learning for Semantic Segmentation

Contrastive learning has shown superior performance in embedding global ...

10 Ho Hin Lee, et al. ∙

research

∙ 12/23/2020

Multi-Contrast Computed Tomography Healthy Kidney Atlas

The construction of three-dimensional multi-modal tissue maps provides a...

13 Ho Hin Lee, et al. ∙

research

∙ 12/23/2020

RAP-Net: Coarse-to-Fine Multi-Organ Segmentation with Single Random Anatomical Prior

Performing coarse-to-fine abdominal multi-organ segmentation facilitates...

0 Ho Hin Lee, et al. ∙

research

∙ 12/05/2020

Development and Characterization of a Chest CT Atlas

A major goal of lung cancer screening is to identify individuals with pa...

0 Kaiwen Xu, et al. ∙

research

∙ 11/02/2020

CaCL: Class-aware Codebook Learning for Weakly Supervised Segmentation on Diffuse Image Patterns

Weakly supervised learning has been rapidly advanced in biomedical image...

0 Ruining Deng, et al. ∙

research

∙ 12/01/2019

Stochastic tissue window normalization of deep learning on computed tomography

Tissue window filtering has been widely used in deep learning for comput...

25 Yuankai Huo, et al. ∙

research

∙ 09/11/2019

Distanced LSTM: Time-Distanced Gates in Long Short-Term Memory Models for Lung Cancer Detection

The field of lung nodule detection and cancer prediction has been rapidl...

0 Riqiang Gao, et al. ∙

research

∙ 04/03/2019

Stratum: A Serverless Framework for Lifecycle Management of Machine Learning based Data Analytics Tasks

With the proliferation of machine learning (ML) libraries and frameworks...

0 Anirban Bhattacharjee, et al. ∙

research

∙ 03/28/2019

3D Whole Brain Segmentation using Spatially Localized Atlas Network Tiles

Detailed whole brain segmentation is an essential quantitative technique...

10 Yuankai Huo, et al. ∙

research

∙ 02/21/2019

Lung Cancer Detection using Co-learning from Chest CT Images and Clinical Demographics

Early detection of lung cancer is essential in reducing mortality. Recen...

10 Jiachen Wang, et al. ∙

research

∙ 12/10/2018

Montage based 3D Medical Image Retrieval from Traumatic Brain Injury Cohort using Deep Convolutional Neural Network

Brain imaging analysis on clinically acquired computed tomography (CT) i...

0 Cailey I. Kerley, et al. ∙

research

∙ 11/10/2018

Coronary Calcium Detection using 3D Attention Identical Dual Deep Network Based on Weakly Supervised Learning

Coronary artery calcium (CAC) is biomarker of advanced subclinical coron...

0 Yuankai Huo, et al. ∙

research

∙ 11/09/2018

Splenomegaly Segmentation on Multi-modal MRI using Deep Convolutional Networks

The findings of splenomegaly, abnormal enlargement of the spleen, is a n...

0 Yuankai Huo, et al. ∙

research

∙ 10/15/2018

SynSeg-Net: Synthetic Segmentation Without Target Modality Ground Truth

A key limitation of deep convolutional neural networks (DCNN) based imag...

0 Yuankai Huo, et al. ∙

research

∙ 06/01/2018

Spatially Localized Atlas Network Tiles Enables 3D Whole Brain Segmentation from Limited Data

Whole brain segmentation on a structural magnetic resonance imaging (MRI...

0 Yuankai Huo, et al. ∙

research

∙ 12/22/2017

A Data Colocation Grid Framework for Big Data Medical Image Processing - Backend Design

When processing large medical imaging studies, adopting high performance...

0 Shunxing Bao, et al. ∙

research

∙ 12/20/2017

Adversarial Synthesis Learning Enables Segmentation Without Target Modality Ground Truth

A lack of generalizability is one key limitation of deep learning based ...

0 Yuankai Huo, et al. ∙

research

∙ 12/02/2017

Improved Stability of Whole Brain Surface Parcellation with Multi-Atlas Segmentation

Whole brain segmentation and cortical surface parcellation are essential...

0 Yuankai Huo, et al. ∙

research

∙ 12/02/2017

Splenomegaly Segmentation using Global Convolutional Kernels and Conditional Generative Adversarial Networks

Spleen volume estimation using automated image segmentation technique ma...

0 Yuankai Huo, et al. ∙

Shunxing Bao

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