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Auxiliary Diagnosis of Papillary Thyroid Carcinoma Based on Spectral Phenotype

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Phenomics 2023年第5期3卷 469-484页

作者： Bailiang Zhao Yan Wang Menghan Hu Yue Wu Jiannan Liu Qingli Li Min Dai Wendell QSun Guangtao Zhai Shanghai Key Laboratory of Multidimensional Information Processing East China Normal UniversityShanghai 200241China School of Health Science and Engineering University of Shanghai for Science and TechnologyShanghai 200093China Department of Pathology The Second People’s Hospital of WuhuWuhu 241000AnhuiChina Ophthalmology Department Shanghai Ninth People’s HospitalShanghai Jiao Tong University School of MedicineShanghai 610101China Department of Oral Maxillofacial Head Neck Oncology Shanghai Ninth People’s HospitalShanghai Jiao Tong University School of MedicineShanghai 200011China Institute of Image Communication and Information Processing Shanghai Jiao Tong UniversityShanghai 200240China

Thyroid cancer,a common endocrine malignancy,is one of the leading death causes among endocrine *** diagnosis of pathological section analysis suffers from diagnostic delay and cumbersome operating ***,we intend to construct the models based on spectral data that can be potentially used for rapid intraoperative papillary thyroid carcinoma(PTC)diagnosis and characterize PTC *** alleviate any concerns pathologists may have about using the model,we conducted an analysis of the used bands that can be interpreted pathologically.A spectra acquisition system was first built to acquire spectra of pathological section images from 91 *** obtained spectral dataset contains 217 spectra of normal thyroid tissue and 217 spectra of PTC *** data of the corresponding patients were collected for subsequent model interpretability *** experiment has been approved by the Ethics Review Committee of the Wuhu Hospital of East China Normal *** spectral preprocessing method was used to process the spectra,and the preprocessed signal respectively optimized by the first and secondary informative wavelengths selection was used to develop the PTC detection *** PTC detection model using mean centering(MC)and multiple scattering correction(MSC)has optimal performance,and the reasons for the good performance were analyzed in combination with the spectral acquisition process and composition of the test *** model interpretable analysis,the near-ultraviolet band selected for modeling corresponds to the location of amino acid absorption peak,and this is consistent with the clinical phenomenon of significantly lower amino acid concentrations in PTC ***,the absorption peak of hemoglobin selected for modeling is consistent with the low hemoglobin index in PTC *** addition,the correlation analysis was performed between the selected wavelengths and the clinical data,and the results show:the ref

关键词： Interpretable pathologic model Pathological analysis Intraoperative detection Spectral phenotype

Multi-Wavelength Narrow Linewidth Random Fiber Laser Based on Fiber Bragg Grating Fabry-Perot Filter

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Multi-Wavelength Narrow Linewidth Random Fiber Laser Based o...

International Conference on Information Science and Technology (ICIST)

作者： Sokliep Pheng Luo Xiaonan Zhongshuai Wang Yijie Zhu Zetao Jiang School of Information and Communication Guilin University of Electronic Technology Guilin China Guangxi Key Laboratory of Intelligent Processing of Computer Image and Graphics Guilin University of Electronic Technology Guilin China School of Computer Science and Information Security Guilin University of Electronic Technology Guilin China

ISBN: (数字)9781728155586

ISBN: (纸本)9781728155593

Recently, multi-wavelength narrow linewidth random fiber laser has very interested for every researcher in this field, because of their useful advantages application, such as high-resolution spectroscopy and fiber optic sensing. In this paper, the standard single-mode fiber is used to form a half-opened cavity structure for generating the narrow linewidth random fiber laser and used the FBG-FP as a filter to form the narrow linewidth RFL into multi-wavelength. Firstly, we used the Rayleigh scattering that processed as well as in a standard single-mode fiber to provide random distribution feedback at the same time while using erbium-doped fiber (EDF) to provide the gain or amplification for achieving a broadband random laser output. Then, FBG-FP is added to the half-open cavity random laser structure. The multi-wavelength and narrow linewidth RFL can be achieved when the broadband RFL goes through the FBG-FP. In this paper we have generated the multi-wavelength narrow linewidth random fiber laser which has more than 10 wavelengths and the 3dB bandwidth is less than 0.01 nm and the mode separation of each wavelength is 0.04nm.

关键词： Fiber gratings Erbium-doped fiber lasers Optical fiber couplers Optical fiber amplifiers

Low-Threshold, Multiple High-Order Harmonics Fiber Laser Employing Cr2si2te6 Saturable Absorber

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SSRN

SSRN 2022年

作者： Xu, Nannan Shang, Xinxin Sun, Shuo Yang, Fuhao Fan, Weiyu Zhang, Huanian Li, Dengwang Shandong Province Key Laboratory of Medical Physics and Image Processing Technology School of Physics and Electronics Shandong Normal University Jinan250014 China Shandong Provincial Key Laboratory of Optics and Photonic Device School of Physics and Electronics Shandong Normal University Jinan250014 China School of Physics and Optoelectronic Engineering Shandong University of Technology Zibo255049 China

Abundant research findings have proved the value of two-dimensional (2D) materials in the research of nonlinear optics within fiber lasers. However, there are two problems, how to reduce the start-up threshold and improve the damage threshold of fiber lasers based on 2D materials, that researchers have always been trying to solve. A 15.1-mW low-threshold mode-locked fiber laser based on Cr2Si2Te6 saturable absorber (SA) prepared by liquid-phase exfoliation method is demonstrated successfully in this work. This provides a handy and economical method to produce SAs with low insertion loss and low saturation intensity. Besides, multiple high-order harmonics from fundamental frequency (12.6 MHz) to 49th-order harmonic (617.6 MHz) mode-locked operations are recorded. The experimental results indicate the excellent potential of Cr2Si2Te6 in exploring the soliton dynamics, harmonic mode-locking and other nonlinear effects in fiber lasers as an optical modulator. © 2022, The Authors. All rights reserved.

关键词： Fiber lasers

Accurate Retinal Vessel Segmentation via Octave Convolution Neural Network

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arXiv 2019年

作者： Fan, Zhun Mo, Jiajie Qiu, Benzhang Li, Wenji Zhu, Guijie Li, Chong Hu, Jianye Rong, Yibiao Chen, Xinjian Department of Electrical and Information Engineering Shantou University Shantou515063 China Guangdong Provincial Key Laboratory of Digital Signal and Image Processing College of Engineering Shantou University Shantou515063 China School of Electrical and Information Engineering Soochow University Suzhou215006 China State Key Laboratory of Radiation Medicine and Protection Soochow University Suzhou215123 China

Retinal vessel segmentation is a crucial step in diagnosing and screening various diseases, including diabetes, ophthalmologic diseases, and cardiovascular diseases. In this paper, we propose an effective and efficient method for vessel segmentation in color fundus images using encoder-decoder based octave convolution network. Compared with other convolution networks utilizing vanilla convolution for feature extraction, the proposed method adopts octave convolution for learning multiplespatial-frequency features, thus can better capture retinal vasculatures with varying sizes and shapes. It is demonstrated that the feature maps of low-frequency kernels respond mainly to the major vascular tree, whereas the high-frequency feature maps can better capture the fine details of thin vessels. To provide the network the capability of learning how to decode multifrequency features, we extend octave convolution and propose a new operation named octave transposed convolution. A novel architecture of convolutional neural network is proposed based on the encoder-decoder architecture of UNet, which can generate high resolution vessel segmentation in one single forward feeding. The proposed method is evaluated on four publicly available datasets, including DRIVE, STARE, CHASE DB1, and HRF. Extensive experimental results demonstrate that the proposed approach achieves better or comparable performance to the stateof-the-art methods with fast processing speed. Copyright © 2019, The Authors. All rights reserved.

关键词： Convolution

MULTI-SCALE FEATURE LEARNING BASED ON NON-CONTRST CT FOR PANCREATIC LESIONS DETECTION

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MULTI-SCALE FEATURE LEARNING BASED ON NON-CONTRST CT FOR PAN...

第十六届国际体视学与图像分析学术会议

作者： Tian YAN Geye TANG Lidu LIANG Jianhua MA Yi GAO Chenjie ZHOU Shulong LI School of Biomedical Engineering Guangdong Provincial Key Laboratory of Medical Image ProcessingGuangdong Province Engineering Laboratory for Medical Imaging and Diagnostic TechnologySouthern Medical University General Surgery Center Department of Hepatobiliary Surgery ⅡGuangdong Provincial Research Center for Artificial Organ and Tissue EngineeringGuangzhou Clinical Research and Transformation Center for Artificial LiverInstitute of Regenerative MedicineZhujiang HospitalSouthern Medical University State Key Laboratory of Organ Failure Research Southern Medical University

Pancreatic cancer is one of the most malignant tumors with poor prognosis and mortality also close to the morbidity,mainly because of the difficulty of early diagnosis and timely treatment in localized *** is clinically important to develop a non-contrast CT(NCCT)-based pancreatic lesion detection model,which would be expected as an intelligent tool for realizing the early ***,it poses the great challenge,because abdominal NCCT presents low contrast intensity for pancreas and its lesions and complex anatomical ***,we design a multiscale feature learning network(MSFL) with Resnet50 and feature pyramid network(FPN) as backbone,by adding multiscale atrous convolutions to expand different receptive fields,contextual attention to perceive contextual information,channel attention and spatial attention to focus on important channels and spatial *** MSFL is used as the feature extractor to propose the NCCT-based pancreatic lesion detection model based on Faster R-CNN as baseline model,to achieve accurate detection of pancreatic *** model with the new MSFL as feature extractor obtains the best performance with recall(75.40%),precision(40.84%),F1 score(51.17%),F2 score(62.86%) and Ap50(60.19%) at image level,and also the best results for recall(85.27%),precision(68.21%),F1 score(77.96%),F2 score(85.26%) and Ap50(60.19%) at patient level,which are superior to conventional object detection *** new model has achieved good performance,which implies that it has high application value,and is expected to be developed as an intelligent method for early detection of pancreatic cancer.

关键词： pancreatic cancer lesion detection atrous convolution multi-scale feature learning attention mechanism

Automated strabismus detection for telemedicine applications

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arXiv 2018年

作者： Lu, Jiewei Fan, Zhun Zheng, Ce Feng, Jingan Huang, Longtao Li, Wenji Goodman, Erik D. Guangdong Provincial Key Laboratory of Digital Signal and Image Processing College of Engineering Shantou University Shantou515063 China Ophthalmology of Shanghai Children's Hospital Shang Hai China BEACON Center for the Study of Evolution in Action Michigan State University East LansingMI48824 United States

Strabismus is one of the most influential ophthalmologic diseases in human's life. Timely detection of strabismus contributes to its prognosis and treatment. Telemedicine, which has great potential to alleviate the growing demand of the diagnosis of ophthalmologic diseases, is an effective method to achieve timely strabismus detection. In this paper, a tele strabismus dataset is established by the ophthalmologists. Then an end-to-end framework named as RF-CNN is proposed to achieve automated strabismus detection on the established tele strabismus dataset. RF-CNN first performs eye region segmentation on each individual image, and further classifies the segmented eye regions with deep neural networks. The experimental results on the established tele strabismus dataset demonstrates that the proposed RF-CNN can have a good performance on automated strabismus detection for telemedicine application. Code is made publicly available at: https://***/jieWeiLu/Strabismus-Detection-for-Telemedicine-Application. Copyright © 2018, The Authors. All rights reserved.

关键词： Telemedicine

A TWO LAYERED DATA ASSOCIATION APPROACH FOR BALL TRACKING

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A TWO LAYERED DATA ASSOCIATION APPROACH FOR BALL TRACKING

IEEE International Conference on Acoustics, Speech and Signal processing

作者： Xiangzeng Zhou Qiang Huang Lei Xie Stephen Cox Shaanxi Provincial Key Laboratory of Speech & Image Information Processing (SAIIP) School of Computer Science Northwestern Polytechnical University Xi'an 710072 P. R. China School of Computing Sciences University of East Anglia Norwich NR4 7TJ United Kingdom

ISBN: (纸本)9781479903573

Ball-tracking is a key technology in processing and analyzing a ball game. Because of the complexity of visual scenes, a large number of objects are usually selected as candidates for the ball, leading to incorrect identification, and conversely, the true position of the ball may sometimes be missed. In this paper, we propose a two layered data association method to improve the robustness of ball-tracking. At a local layer, we use a sliding window based Token Transfer method to generate a set of sub-trajectory candidates. At a global layer, a single ball trajectory is obtained by applying a dynamic programming based splice method to a graph consisting of the sub-trajectory candidates. We evaluated our approach on tennis matches from the Australian Open and the U.S. Open, and the results obtained show that our approach outperforms the state-of-art approach by around 30 %.

关键词： data association tennis ball tracking trajectory layered data association tennis Ball Device Component trajectory roller path tracking sliding windows key technology associations Association

Fast signal recovery from saturated measurements by linear loss and nonconvex penalties

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arXiv 2018年

作者： He, Fan Huang, Xiaolin Liu, Yipeng Yan, Ming Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University The MOE Key Laboratory of System Control and Information Processing Shanghai200240 China School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu611731 China The Department of Computational Mathematics Science and Engineering Michigan State University MI United States

Sign information is the key to overcoming the inevitable saturation error in compressive sensing systems, which causes information loss and results in bias. For sparse signal recovery from saturation, we propose to use a linear loss to improve the effectiveness from existing methods that utilize hard constraints/hinge loss for sign consistency. Due to the use of linear loss, an analytical solution in the update progress is obtained, and some nonconvex penalties are applicable, e.g., the minimax concave penalty, the 0 norm, and the sorted 1 norm. Theoretical analysis reveals that the estimation error can still be bounded. Generally, with linear loss and nonconvex penalties, the recovery performance is significantly improved, and the computational time is largely saved, which is verified by the numerical experiments. Copyright © 2018, The Authors. All rights reserved.

关键词： Compressed sensing

A hierarchical image matting model for blood vessel segmentation in fundus images

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arXiv 2017年

作者： Fan, Zhun Lu, Jiewei Li, Wenji Wei, Caimin Huang, Han Cai, Xinye Chen, Xinjian Guangdong Provincial Key Laboratory of Digital Signal and Image Processing College of Engineering Shantou University Shan'tou515063 China Department of Mathematics Shantou University Shan'tou515063 China School of Software Engineering South China University of Technology Guang'zhou510006 China College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Jiang'su210016 China Medical Image Processing and Analysis Lab School of Electronics and Information Engineering Soochow University Su'zhou215006 China

In this paper, a hierarchical image matting model is proposed to extract blood vessels from fundus images. More specifically, a hierarchical strategy utilizing the continuity and extendibility of retinal blood vessels is integrated into the image matting model for blood vessel segmentation. Normally the matting models require the user specified trimap, which separates the input image into three regions manually: the foreground, background and unknown regions. However, since creating a user specified trimap is a tedious and time-consuming task, region features of blood vessels are used to generate the trimap automatically in this paper. The proposed model has low computational complexity and outperforms many other state-of-art supervised and unsupervised methods in terms of accuracy, which achieves a vessel segmentation accuracy of 96.0%, 95.7% and 95.1% in an average time of 10.72s, 15.74s and 50.71s on images from three publicly available fundus image datasets DRIVE, STARE, and CHASE_DB1, respectively. Copyright © 2017, The Authors. All rights reserved.

关键词： Blood vessels