Search Results for author: Agnes B. Fogo

Found 17 papers, 15 papers with code

Circle Representation for Medical Instance Object Segmentation

1 code implementation18 Mar 2024 Juming Xiong, Ethan H. Nguyen, Yilin Liu, Ruining Deng, Regina N Tyree, Hernan Correa, Girish Hiremath, Yaohong Wang, Haichun Yang, Agnes B. Fogo, Yuankai Huo

Recently, circle representation has been introduced for medical imaging, designed specifically to enhance the detection of instance objects that are spherically shaped (e. g., cells, glomeruli, and nuclei).

Instance Segmentation Object +2

CircleSnake: Instance Segmentation with Circle Representation

1 code implementation2 Nov 2022 Ethan H. Nguyen, Haichun Yang, Zuhayr Asad, Ruining Deng, Agnes B. Fogo, Yuankai Huo

Circle representation has recently been introduced as a medical imaging optimized representation for more effective instance object detection on ball-shaped medical objects.

Instance Segmentation object-detection +3

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

1 code implementation30 Aug 2022 Tianyuan Yao, Chang Qu, Jun Long, Quan Liu, Ruining Deng, Yuanhan Tian, Jiachen Xu, Aadarsh Jha, Zuhayr Asad, Shunxing Bao, Mengyang Zhao, Agnes B. Fogo, Bennett A. Landman, Haichun Yang, Catie Chang, Yuankai Huo

In order to extract and separate compound figures into usable individual images for downstream learning, we propose a simple compound figure separation (SimCFS) framework without using the traditionally required detection bounding box annotations, with a new loss function and a hard case simulation.

Contrastive Learning Image Augmentation +2

Omni-Seg: A Scale-aware Dynamic Network for Renal Pathological Image Segmentation

1 code implementation27 Jun 2022 Ruining Deng, Quan Liu, Can Cui, Tianyuan Yao, Jun Long, Zuhayr Asad, R. Michael Womick, Zheyu Zhu, Agnes B. Fogo, Shilin Zhao, Haichun Yang, Yuankai Huo

The contribution of this paper is three-fold: (1) a novel scale-aware controller is proposed to generalize the dynamic neural network from single-scale to multi-scale; (2) semi-supervised consistency regularization of pseudo-labels is introduced to model the inter-scale correlation of unannotated tissue types into a single end-to-end learning paradigm; and (3) superior scale-aware generalization is evidenced by directly applying a model trained on human kidney images to mouse kidney images, without retraining.

Image Segmentation Segmentation +1

Glo-In-One: Holistic Glomerular Detection, Segmentation, and Lesion Characterization with Large-scale Web Image Mining

1 code implementation31 May 2022 Tianyuan Yao, Yuzhe Lu, Jun Long, Aadarsh Jha, Zheyu Zhu, Zuhayr Asad, Haichun Yang, Agnes B. Fogo, Yuankai Huo

To leverage the performance of the Glo-In-One toolkit, we introduce self-supervised deep learning to glomerular quantification via large-scale web image mining.

Segmentation

Holistic Fine-grained GGS Characterization: From Detection to Unbalanced Classification

1 code implementation31 Jan 2022 Yuzhe Lu, Haichun Yang, Zuhayr Asad, Zheyu Zhu, Tianyuan Yao, Jiachen Xu, Agnes B. Fogo, Yuankai Huo

Recent studies have demonstrated the diagnostic and prognostic values of global glomerulosclerosis (GGS) in IgA nephropathy, aging, and end-stage renal disease.

Classification

Circle Representation for Medical Object Detection

1 code implementation22 Oct 2021 Ethan H. Nguyen, Haichun Yang, Ruining Deng, Yuzhe Lu, Zheyu Zhu, Joseph T. Roland, Le Lu, Bennett A. Landman, Agnes B. Fogo, Yuankai Huo

Compared with the conventional bounding box representation, the proposed bounding circle representation innovates in three-fold: (1) it is optimized for ball-shaped biomedical objects; (2) The circle representation reduced the degree of freedom compared with box representation; (3) It is naturally more rotation invariant.

Medical Object Detection Object +1

Compound Figure Separation of Biomedical Images with Side Loss

1 code implementation19 Jul 2021 Tianyuan Yao, Chang Qu, Quan Liu, Ruining Deng, Yuanhan Tian, Jiachen Xu, Aadarsh Jha, Shunxing Bao, Mengyang Zhao, Agnes B. Fogo, Bennett A. Landman, Catie Chang, Haichun Yang, Yuankai Huo

Our technical contribution is three-fold: (1) we introduce a new side loss that is designed for compound figure separation; (2) we introduce an intra-class image augmentation method to simulate hard cases; (3) the proposed framework enables an efficient deployment to new classes of images, without requiring resource extensive bounding box annotations.

Contrastive Learning Image Augmentation +1

Improve Global Glomerulosclerosis Classification with Imbalanced Data using CircleMix Augmentation

1 code implementation16 Jan 2021 Yuzhe Lu, Haichun Yang, Zheyu Zhu, Ruining Deng, Agnes B. Fogo, Yuankai Huo

Different from the recently proposed CutMix method, the CircleMix augmentation is optimized for the ball-shaped biomedical objects, such as glomeruli.

Classification Data Augmentation +1

EasierPath: An Open-source Tool for Human-in-the-loop Deep Learning of Renal Pathology

1 code implementation28 Jul 2020 Zheyu Zhu, Yuzhe Lu, Ruining Deng, Haichun Yang, Agnes B. Fogo, Yuankai Huo

Inspired by the recent "human-in-the-loop" strategy, we developed EasierPath, an open-source tool to integrate human physicians and deep learning algorithms for efficient large-scale pathological image quantification as a loop.

object-detection Object Detection +1

Instance Segmentation for Whole Slide Imaging: End-to-End or Detect-Then-Segment

2 code implementations7 Jul 2020 Aadarsh Jha, Haichun Yang, Ruining Deng, Meghan E. Kapp, Agnes B. Fogo, Yuankai Huo

In this paper, we assess if the end-to-end instance segmentation framework is optimal for high-resolution WSI objects by comparing Mask-RCNN with our proposed detect-then-segment framework.

Instance Segmentation Segmentation +1

Map3D: Registration Based Multi-Object Tracking on 3D Serial Whole Slide Images

1 code implementation10 Jun 2020 Ruining Deng, Haichun Yang, Aadarsh Jha, Yuzhe Lu, Peng Chu, Agnes B. Fogo, Yuankai Huo

However, the 3D identification and association of large-scale glomeruli on renal pathology is challenging due to large tissue deformation, missing tissues, and artifacts from WSI.

Multi-Object Tracking whole slide images

CircleNet: Anchor-free Detection with Circle Representation

1 code implementation3 Jun 2020 Haichun Yang, Ruining Deng, Yuzhe Lu, Zheyu Zhu, Ye Chen, Joseph T. Roland, Le Lu, Bennett A. Landman, Agnes B. Fogo, Yuankai Huo

In this work, we propose CircleNet, a simple anchor-free detection method with circle representation for detection of the ball-shaped glomerulus.

Object object-detection +1

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