no code implementations • 22 Mar 2024 • Kyle Lucke, Aleksandar Vakanski, Min Xian
In recent years, convolutional neural networks for semantic segmentation of breast ultrasound (BUS) images have shown great success; however, two major challenges still exist.
1 code implementation • 4 Nov 2023 • Longze li, Jiang Chang, Aleksandar Vakanski, Yachun Wang, Tiankai Yao, Min Xian
With the increased use of data-driven approaches and machine learning-based methods in material science, the importance of reliable uncertainty quantification (UQ) of the predicted variables for informed decision-making cannot be overstated.
no code implementations • 27 Aug 2023 • Mohammad Karimzadeh, Aleksandar Vakanski, Min Xian, Boyu Zhang
Despite recent medical advancements, breast cancer remains one of the most prevalent and deadly diseases among women.
no code implementations • 4 Aug 2023 • Bryar Shareef, Min Xian, Aleksandar Vakanski, Haotian Wang
Vision Transformers have an improved capability of capturing global contextual information but may distort the local image patterns due to the tokenization operations.
1 code implementation • 16 May 2023 • Fenghe Tang, Jianrui Ding, Lingtao Wang, Min Xian, Chunping Ning
Our approach enables the effective transfer of probability distribution knowledge to the segmentation network, resulting in improved segmentation accuracy.
no code implementations • 9 Mar 2023 • Shoukun Sun, Min Xian, Fei Xu, Luca Capriotti, Tiankai Yao
Remarkably, our model reduces by 33. 2\%, and 15. 5\% the number of clicks required to surpass an IoU of 0. 95 in the previous state-of-the-art approach on the Berkeley and DAVIS sets, respectively.
Ranked #1 on Interactive Segmentation on DAVIS
no code implementations • 8 Feb 2023 • Shoukun Sun, Fei Xu, Lu Cai, Daniele Salvato, Fidelma Dilemma, Luca Capriotti, Min Xian, Tiankai Yao
In the advanced annular U-10Zr fuel, the lanthanides present as fission gas bubbles.
no code implementations • 24 Jan 2023 • Sujata Butte, Haotian Wang, Aleksandar Vakanski, Min Xian
To address the challenges, we propose a novel approach that enhances the quality of synthetic images by using nuclei topology and contour regularization.
2 code implementations • 24 Oct 2022 • Fenghe Tang, Lingtao Wang, Chunping Ning, Min Xian, Jianrui Ding
However, due to the inherent local characteristics of ordinary convolution operations, U-Net encoder cannot effectively extract global context information.
no code implementations • 2 Sep 2022 • Haotian Wang, Min Xian, Aleksandar Vakanski, Bryar Shareef
Existing deep neural networks for histopathology image synthesis cannot generate image styles that align with different organs, and cannot produce accurate boundaries of clustered nuclei.
no code implementations • 2 May 2022 • Shoukun Sun, Min Xian, Aleksandar Vakanski, Hossny Ghanem
Robust self-training (RST) can augment the adversarial robustness of image classification models without significantly sacrificing models' generalizability.
no code implementations • 13 Jan 2022 • Jiaqiao Shi, Aleksandar Vakanski, Min Xian, Jianrui Ding, Chunping Ning
The accuracy, sensitivity, and specificity of tumor classification is 88. 6%, 94. 1%, and 85. 3%, respectively.
no code implementations • 27 Oct 2021 • Haotian Wang, Min Xian, Aleksandar Vakanski
The proposed topology loss computes gland topology using gland skeletons and markers.
no code implementations • 27 Oct 2021 • Sujata Butte, Haotian Wang, Min Xian, Aleksandar Vakanski
Conditional generative adversarial networks have been applied to generate synthetic histopathology images to alleviate this issue, but current approaches fail to generate clear contours for overlapped and touching nuclei.
no code implementations • 5 Oct 2021 • Boyu Zhang, Aleksandar Vakanski, Min Xian
In healthcare, it is essential to explain the decision-making process of machine learning models to establish the trustworthiness of clinicians.
no code implementations • 30 Sep 2021 • Haotian Wang, Aleksandar Vakanski, Changfa Shi, Min Xian
Separating overlapped nuclei is a major challenge in histopathology image analysis.
no code implementations • 12 Apr 2021 • Lu Cai, Fei Xu, Fidelma Dilemma, Daniel J. Murray, Cynthia A. Adkins, Larry K Aagesen Jr, Min Xian, Luca Caprriot, Tiankai Yao
UZr based metallic nuclear fuel is the leading candidate for next-generation sodium-cooled fast reactors in the United States.
1 code implementation • 4 Mar 2021 • Aleksandar Vakanski, Min Xian
The generalization performance of deep learning models for medical image analysis often decreases on images collected with different devices for data acquisition, device settings, or patient population.
no code implementations • 24 Feb 2021 • Changfa Shi, Min Xian, Xiancheng Zhou, Haotian Wang, Heng-Da Cheng
Both qualitative and quantitative results demonstrate that, in the presence of major pathology, the proposed method is more accurate and robust than state-of-the-art methods.
no code implementations • 27 Sep 2020 • Bryar Shareef, Alex Vakanski, Min Xian, Phoebe E. Freer
Breast tumor segmentation is a critical task in computer-aided diagnosis (CAD) systems for breast cancer detection because accurate tumor size, shape and location are important for further tumor quantification and classification.
no code implementations • 29 Feb 2020 • Yalin Liao, Aleksandar Vakanski, Min Xian, David Paul, Russell Baker
The presented study reviews computational approaches for evaluating patient performance in rehabilitation programs using motion capture systems.
no code implementations • 3 Feb 2020 • Haotian Wang, Min Xian, Aleksandar Vakanski
Separating overlapped nuclei is a major challenge in histopathology image analysis.
3 code implementations • 3 Feb 2020 • Bryar Shareef, Min Xian, Aleksandar Vakanski
The proposed approach outperformed the state-of-the-art approaches in segmenting small breast tumors.
no code implementations • 23 Oct 2019 • Fei Xu, Yingtao Zhang, Min Xian, H. D. Cheng, Boyu Zhang, Jianrui Ding, Chunping Ning, Ying Wang
Then we refine the layers by integrating a non-semantic breast anatomy model to solve the problems of incomplete mammary layers.
1 code implementation • 20 Oct 2019 • Aleksandar Vakanski, Min Xian, Phoebe Freer
The salient attention model has potential to enhance accuracy and robustness in processing medical images of other organs, by providing a means to incorporate task-specific knowledge into deep learning architectures.
Ranked #1 on Tumor Segmentation on BUS 2017 Dataset B
no code implementations • 18 Jun 2019 • Fei Xu, Yingtao Zhang, Min Xian, H. D. Cheng, Boyu Zhang, Jianrui Ding, Chunping Ning, Ying Wang
First, we model breast anatomy and decompose breast ultrasound image into layers using Neutro-Connectedness; then utilize the layers to generate the foreground and background maps; and finally propose a novel objective function to estimate the tumor saliency by integrating the foreground map, background map, adaptive center bias, and region-based correlation cues.
no code implementations • 27 Jun 2018 • Fei Xu, Min Xian, Yingtao Zhang, Kuan Huang, H. D. Cheng, Boyu Zhang, Jianrui Ding, Chunping Ning, Ying Wang
Automatic tumor segmentation of breast ultrasound (BUS) image is quite challenging due to the complicated anatomic structure of breast and poor image quality.
no code implementations • 27 Jun 2018 • Yusheng Luo, Min Xian, Manish Mohanpurkar, Bishnu P. Bhattarai, Anudeep Medam, Rahul Kadavil, Rob Hovsapian
Optimal scheduling of hydrogen production in dynamic pricing power market can maximize the profit of hydrogen producer; however, it highly depends on the accurate forecast of hydrogen consumption.
no code implementations • 13 Feb 2018 • Boyu Zhang, Yingtao Zhang, H. D. Cheng, Min Xian, Shan Gai, Olivia Cheng, Kuan Huang
In this survey paper, we classify the existing methods by their principles and discuss the current research status and point out the future research trend in-depth.
1 code implementation • 9 Jan 2018 • Min Xian, Yingtao Zhang, H. D. Cheng, Fei Xu, Kuan Huang, Boyu Zhang, Jianrui Ding, Chunping Ning, Ying Wang
Breast ultrasound (BUS) image segmentation is challenging and critical for BUS Comput-er-Aided Diagnosis (CAD) systems.
no code implementations • 4 Apr 2017 • Min Xian, Yingtao Zhang, H. D. Cheng, Fei Xu, Boyu Zhang, Jianrui Ding
Breast cancer is one of the leading causes of cancer death among women worldwide.
no code implementations • 19 Dec 2015 • Min Xian, Yingtao Zhang, H. D. Cheng, Fei Xu, Jianrui Ding
Interactive image segmentation is a challenging task and receives increasing attention recently; however, two major drawbacks exist in interactive segmentation approaches.
no code implementations • 24 Aug 2015 • Jianrui Ding, Min Xian, H. D. Cheng, Yang Li, Fei Xu, Yingtao Zhang
And the dynamic features are formed by using the information of its neighbor frames in the sequence.
no code implementations • 11 Jul 2015 • Hongkai Yu, Youjie Zhou, Hui Qian, Min Xian, Yuewei Lin, Dazhou Guo, Kang Zheng, Kareem Abdelfatah, Song Wang
In this paper, we develop a new LooseCut algorithm that can handle cases where the input bounding box only loosely covers the foreground object.