no code implementations • 21 Jul 2023 • Quan Liu, Hanyu Zheng, Brandon T. Swartz, Ho Hin Lee, Zuhayr Asad, Ivan Kravchenko, Jason G. Valentine, Yuankai Huo
However, the digital design of the metamaterial neural network (MNN) is fundamentally limited by its physical limitations, such as precision, noise, and bandwidth during fabrication.
no code implementations • 3 Jul 2023 • Can Cui, Yaohong Wang, Shunxing Bao, Yucheng Tang, Ruining Deng, Lucas W. Remedios, Zuhayr Asad, Joseph T. Roland, Ken S. Lau, Qi Liu, Lori A. Coburn, Keith T. Wilson, Bennett A. Landman, Yuankai Huo
Many anomaly detection approaches, especially deep learning methods, have been recently developed to identify abnormal image morphology by only employing normal images during training.
no code implementations • 5 Jun 2023 • Tianyuan Yao, Francois Rheault, Leon Y Cai, Vishwesh Nath, Zuhayr Asad, Nancy Newlin, Can Cui, Ruining Deng, Karthik Ramadass, Andrea Shafer, Susan Resnick, Kurt Schilling, Bennett A. Landman, Yuankai Huo
From the experimental results, the proposed data-driven framework outperforms the existing benchmarks in repeated fODF estimation.
1 code implementation • 31 May 2023 • Ruining Deng, Yanwei Li, Peize Li, Jiacheng Wang, Lucas W. Remedios, Saydolimkhon Agzamkhodjaev, Zuhayr Asad, Quan Liu, Can Cui, Yaohong Wang, Yihan Wang, Yucheng Tang, Haichun Yang, Yuankai Huo
The contribution of this paper is threefold: (1) We proposed a molecular-empowered learning scheme for multi-class cell segmentation using partial labels from lay annotators; (2) The proposed method integrated Giga-pixel level molecular-morphology cross-modality registration, molecular-informed annotation, and molecular-oriented segmentation model, so as to achieve significantly superior performance via 3 lay annotators as compared with 2 experienced pathologists; (3) A deep corrective learning (learning with imperfect label) method is proposed to further improve the segmentation performance using partially annotated noisy data.
1 code implementation • 23 May 2023 • Haoju Leng, Ruining Deng, Zuhayr Asad, R. Michael Womick, Haichun Yang, Lipeng Wan, Yuankai Huo
Our proposed method's innovative contribution is two-fold: (1) a Docker is released for an end-to-end slide-wise multi-tissue segmentation for WSIs; and (2) the pipeline is deployed on a GPU to accelerate the prediction, achieving better segmentation quality in less time.
1 code implementation • 2 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.
1 code implementation • 30 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.
1 code implementation • 27 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.
1 code implementation • 31 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.
no code implementations • 25 Mar 2022 • Can Cui, Haichun Yang, Yaohong Wang, Shilin Zhao, Zuhayr Asad, Lori A. Coburn, Keith T. Wilson, Bennett A. Landman, Yuankai Huo
The rapid development of diagnostic technologies in healthcare is leading to higher requirements for physicians to handle and integrate the heterogeneous, yet complementary data that are produced during routine practice.
no code implementations • 8 Mar 2022 • Can Cui, Han Liu, Quan Liu, Ruining Deng, Zuhayr Asad, Yaohong WangShilin Zhao, Haichun Yang, Bennett A. Landman, Yuankai Huo
Thus, there are still open questions on how to effectively predict brain cancer survival from the incomplete radiological, pathological, genomic, and demographic data (e. g., one or more modalities might not be collected for a patient).
1 code implementation • 31 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.
1 code implementation • 13 Jan 2022 • Kaifeng Pang, Zuhayr Asad, Shilin Zhao, Yuankai Huo
Such algorithms can be summarized as (1) patch-level MSI/MSS prediction, and (2) patient-level aggregation.
1 code implementation • 23 Dec 2021 • Ruining Deng, Quan Liu, Can Cui, Zuhayr Asad, Haichun Yang, Yuankai Huo
Computer-assisted quantitative analysis on Giga-pixel pathology images has provided a new avenue in histology examination.
no code implementations • 13 Dec 2021 • Jiachen Xu, Junlin Guo, James Zimmer-Dauphinee, Quan Liu, Yuxuan Shi, Zuhayr Asad, D. Mitchell Wilkes, Parker VanValkenburgh, Steven A. Wernke, Yuankai Huo
Recently, systematic manual survey of satellite and aerial imagery has enabled continuous distributional views of archaeological phenomena at interregional scales.
no code implementations • 26 Aug 2021 • Cam Nguyen, Zuhayr Asad, Yuankai Huo
For a more comprehensive analysis, we also compare the transformer-based models with six major traditional CNN-based models.