Article
Oncology
Reem Altaf, Umair Ilyas, Anmei Ma, Meiqi Shi
Summary: In this study, bioinformatics analysis was used to evaluate four datasets for differentially expressed genes (DEGs) associated with non-small cell lung cancer (NSCLC). Ten significant DEGs were identified and their expression was validated. Gene-gene and drug-gene network analysis revealed important interactions and potential drug targets. This study highlights the importance of systemic genetics in identifying potential targeted therapies for NSCLC.
FRONTIERS IN ONCOLOGY
(2023)
Article
Genetics & Heredity
Weitao Hu, Taiyong Fang, Xiaoqing Chen
Summary: This study identified DEGs associated with ulcerative colitis (UC) using bioinformatics analysis, providing potential diagnostic and therapeutic targets. The DEGs, hub genes and miRNAs identified may serve as biomarkers for UC, but further research is needed to understand their biological roles in the disease.
FRONTIERS IN GENETICS
(2022)
Article
Medicine, General & Internal
Guan Lin, Zhang Xinhe, Tian Haoyu, Li Yiling
Summary: This study identified aberrantly methylated-differentially expressed genes and related pathways involved in cholangiocarcinoma (CCA). The analysis of mRNA expression and methylation profiling data revealed a number of genes that showed differential expression and methylation in CCA. Functional enrichment analysis and protein-protein interaction network analysis identified several pathways and hub genes associated with these genes. The findings of this study provide potential biomarkers for the accurate diagnosis and treatment of CCA.
Article
Rheumatology
Jun Inamo
Summary: This study investigated the relationship between different types of autoantibodies and gene expression profiles in skin lesions of patients with Systemic Sclerosis (SSc), identifying specific dysregulated pathways associated with each autoantibody type. By analyzing gene expression data, the study revealed potential new therapeutic targets for SSc based on specific autoantibody profiles.
Article
Oncology
Wesley Ladeira Caputo, Milena Cremer de Souza, Caroline Rodrigues Basso, Valber de Albuquerque Pedrosa, Fabio Rodrigues Ferreira Seiva
Summary: This study provides a comprehensive analysis of differentially expressed genes in hepatocellular carcinoma (HCC), identifying potential therapeutic targets and opportunities for drug repurposing.
Article
Multidisciplinary Sciences
Douglas Terra Machado, Otavio Jose Bernardes Brustolini, Yasmmin Cortes Martins, Marco Antonio Grivet Mattoso Maia, Ana Tereza Ribeiro de Vasconcelos
Summary: DEGRE is a user-friendly tool that considers fixed and random effects on individuals in the experimental design of RNA-Seq research to infer differentially expressed genes (DEGs). It preprocesses the data and applies generalized linear mixed models (GLMMs) to provide inference for DEGs. This tool efficiently removes genes that could impact the inference and offers improved assessment measures in cases with higher biological variability.
Article
Genetics & Heredity
Zhenhua Lu, Lingbing Meng, Zhen Sun, Xiaolei Shi, Weiwei Shao, Yangyang Zheng, Xinglei Yao, Jinghai Song
Summary: The study analyzed gene expression profiles of adipose tissues from obese patients and non-obese controls, revealing that inflammation in adipose tissues may be primarily caused by an increase in macrophages and a decrease in gamma delta T cells, leading to the occurrence of obesity-related complications. By constructing a protein-protein interaction network, central genes related to obesity were identified, along with chemicals that may contribute to obesity.
FRONTIERS IN GENETICS
(2021)
Article
Genetics & Heredity
Huaifeng Liu, Yu Gao, Shangshang Hu, Zhengran Fan, Xianggang Wang, Shujing Li
Summary: The study identified 563 DERGs in LIHC patients, with some genes significantly associated with survival rate. Consistent results from bioinformatics analysis and cell experiments showed that abnormal expression of CSNK1D, CSNK1E, and NPAS2 genes were closely related to the survival rate of LIHC patients.
FRONTIERS IN GENETICS
(2021)
Article
Oncology
Weiqian Guo, Xiaomin Zheng, Lei Hua, Xianbin Zheng, Yangyang Zhang, Bin Sun, Zhenchao Tao, Jin Gao
Summary: Differentiated expressed genes for nasopharyngeal carcinoma were identified and potential biomarkers were explored through bioinformatical analysis. The core genes screened may serve as prognostic and diagnostic biomarkers for NPC.
Article
Clinical Neurology
Xitong Yang, Pengyu Wang, Shanquan Yan, Guangming Wang
Summary: In this study, bioinformatics was used to analyze the pathogenesis of stroke, resulting in the identification of 85 differentially expressed genes and 10 hub genes through PPI network and CytoHubba analysis. Additionally, 5 key miRNAs were predicted as potential biomarkers for ischemic stroke, providing new strategies for clinical therapy.
NEUROLOGICAL SCIENCES
(2022)
Article
Medicine, General & Internal
Hailong Zhou, Jianmin Jiang, Xiaohua Chen, Zhiwei Zhang
Summary: This study investigated the genes, miRNAs, pathways, and miRNA-gene interaction pairs involved in female osteoporosis. The results revealed the important roles of miRNAs and genes in the pathogenesis of osteoporosis, and identified several pathways related to the disease.
Article
Biology
Bokang Ko, Jeremy M. Van Raamsdonk
Summary: Gene expression studies provide valuable insights into biological processes, such as aging. This study shows that pooling individual RNA samples before sequencing can yield similar results as sequencing them individually, reducing the cost of experiments. Analysis of gene expression changes across the genome is a powerful and unbiased tool for understanding molecular mechanisms.
Article
Cardiac & Cardiovascular Systems
Kun Wang, Yancheng Song, Hong Li, Jianshu Song, Shizhong Wang
Summary: This study identified differentially expressed genes associated with ferroptosis in abdominal aortic aneurysm (AAA) through bioinformatics analysis and experimental validation. The findings suggest that IL-6, PRDX1, and SCD might affect the development of AAA by regulating ferroptosis. This research provides insights into the pathogenesis of AAA and potential treatment strategies.
FRONTIERS IN CARDIOVASCULAR MEDICINE
(2022)
Article
Biology
Meiyu Duan, Yueying Wang, Ya Qiao, Yangyang Wang, Xingyuan Pan, Zhuyu Hu, Yanyue Ran, Xian Fu, Yusi Fan, Lan Huang, Fengfeng Zhou
Summary: The transcriptome is a comprehensive reflection of gene expression in a sample. This study proposes a novel approach to understanding the regulatory relationships between transcription factors (TFs) and their target genes (mRNAs) by quantitatively analyzing the differences in their expression levels. By using a multi-input multi-output regression model, this study explores the quantitative transcription regulation relationships of metabolism-related genes. The findings suggest that certain genes can exhibit differential regulation patterns even when their expression levels do not differ significantly, and these "dark biomarkers" may have important implications for disease detection and classification.
COMPUTERS IN BIOLOGY AND MEDICINE
(2022)
Article
Multidisciplinary Sciences
Changsheng Guo, Yuanqing Hua, Zuanhao Qian
Summary: This study identified differentially expressed lncRNAs and genes in Kawasaki disease (KD), as well as constructed ceRNA networks involving miRNAs and mRNAs. The study found specific lncRNAs (PSORS1C3, LINC00999, SNHG5) and genes (GATA3, SOD2, MAPK14, PPARG) that may play a key role in the pathogenesis and development of KD. Validation in a separate dataset showed that intravenous immunoglobulin treatment alleviated the deregulated RNA profiles in KD patients.
Correction
Biochemistry & Molecular Biology
Yi Han, Juze Yang, Xinyi Qian, Wei-Chung Cheng, Shu-Hsuan Liu, Xing Hua, Liyuan Zhou, Yaning Yang, Qingbiao Wu, Pengyuan Liu, Yan Lu
NUCLEIC ACIDS RESEARCH
(2021)
Article
Pharmacology & Pharmacy
Chia-Cheng Su, Shu-Chi Wang, I-Chen Chen, Fang-Yen Chiu, Po-Len Liu, Chi-Han Huang, Kuan-Hua Huang, Shih-Hua Fang, Wei-Chung Cheng, Shu-Pin Huang, Hsin-Chih Yeh, Ching-Chih Liu, Po-Yen Lee, Ming-Yii Huang, Chia-Yang Li
Summary: The study demonstrated that zerumbone effectively attenuates LPS-induced inflammatory response in macrophages both in vitro and ex vivo by suppressing the activation of the ERK-MAPK and NF-kappa B signaling pathways as well as blocking the activation of the NLRP3 inflammasome, suggesting its potential benefits for treating sepsis and inflammasome-related diseases.
FRONTIERS IN PHARMACOLOGY
(2021)
Article
Medicine, Research & Experimental
Shu-Hsuan Liu, Kai-Wen Hsu, Yo-Liang Lai, Yu-Feng Lin, Fang-Hsin Chen, Pei-Hwa Peng, Li-Jie Lin, Heng-Hsiung Wu, Chia-Yang Li, Shu-Chi Wang, Min-Zu Wu, Yuh-Pyng Sher, Wei-Chung Cheng
Summary: The study found that both individual miRNA mimics and the combination of the three miRNA mimics were effective in inhibiting tumor growth and progression, with the combination being more effective than the single miRNA mimics. In lung cancer animal models, the combined miRNA mimics provided significant therapeutic effects in terms of reduced tumor volume and metastasis nodules.
MOLECULAR THERAPY-NUCLEIC ACIDS
(2021)
Article
Oncology
Tsai-Tsen Liao, Wei-Chung Cheng, Chih-Yung Yang, Yin-Quan Chen, Shu-Han Su, Tzu-Yu Yeh, Hsin-Yi Lan, Chih-Chan Lee, Hung-Hsin Lin, Chun-Chi Lin, Ruey-Hwa Lu, Arthur Er-Terg Chiou, Jeng-Kai Jiang, Wei-Lun Hwang
Summary: Metastasis of tumor cells is the leading cause of death in cancer patients, making it crucial to identify molecular tools for the detection and treatment of CSCs. MiR-210 targeting STMN1 to decrease cell elasticity and promote cell motility offers a potential strategy to reduce CSC-oriented metastasis. This study uncovers a miRNA-oriented mechanism regulating cell migration and deformability in CRCSCs beyond the EMT process.
Article
Biochemistry & Molecular Biology
Fen-Lan Wu, Pei-Yi Chu, Guan-Yu Chen, Ke Wang, Wei-Yu Hsu, Azaj Ahmed, Wen-Lung Ma, Wei-Chung Cheng, Yang-Chang Wu, Juan-Cheng Yang
Summary: Aurora kinase A (AURKA) plays a crucial role in proliferation and resistance to cisplatin in cancer cells. Overexpression of AURKA is linked to poor cancer prognosis, making it a target for therapy. Emodin, a natural compound found in rhubarb, is shown to potentially inhibit cancer cell growth and enhance cisplatin therapy in resistant cancers, particularly in ovarian cancer.
CHEMICAL BIOLOGY & DRUG DESIGN
(2022)
Article
Biochemistry & Molecular Biology
Wen-Jen Lin, Pei-Chun Shen, Hsiu-Cheng Liu, Yi-Chun Cho, Min-Kung Hsu, I-Chen Lin, Fang-Hsin Chen, Juan-Cheng Yang, Wen-Lung Ma, Wei-Chung Cheng
Summary: LipidSig is a flexible and user-friendly web server designed to help users identify significant lipid-related features and advance the field of lipid biology through efficient data analysis and exploration of lipid characteristics.
NUCLEIC ACIDS RESEARCH
(2021)
Article
Multidisciplinary Sciences
Po-Yen Lee, Yu-Hung Lai, Po-Len Liu, Ching-Chih Liu, Chia-Cheng Su, Fang-Yen Chiu, Wei-Chung Cheng, Shiuh-Liang Hsu, Kai-Chun Cheng, Li-Yi Chiu, Tzu-En Kao, Chia-Ching Lin, Yo-Chen Chang, Shu-Chi Wang, Chia-Yang Li
Summary: This study found different effects of amantadine HCl on bovine cornea endothelial cells, including inhibiting cell growth, inducing apoptosis, increasing sub-G1 phase growth arrest, causing DNA damage, and inducing endothelial hyperpermeability.
SCIENTIFIC REPORTS
(2021)
Article
Cell Biology
Yuan-Liang Wang, Chuan-Chun Lee, Yi-Chun Shen, Pei-Le Lin, Wan-Rong Wu, You-Zhe Lin, Wei-Chung Cheng, Han Chang, Yu Hung, Yi-Chun Cho, Liang-Chih Liu, Wei-Ya Xia, Jin-Huei Ji, Ji-An Liang, Shu-Fen Chiang, Chang-Gong Liu, Jun Yao, Mien-Chie Hung, Shao-Chun Wang
Summary: The phosphorylation of PCNA on tyrosine 211 was found to regulate DNA metabolism and tumor microenvironment, ultimately triggering an immune response to suppress cancer metastasis.
Article
Biochemistry & Molecular Biology
You-Zhe Lin, Shu-Hsuan Liu, Wan-Rong Wu, Yi-Chun Shen, Yuan-Liang Wang, Chien-Ching Liao, Pei-Le Lin, Han Chang, Liang-Chih Liu, Wei-Chung Cheng, Shao-Chun Wang
Summary: This study identifies miR-4759 as a novel non-coding RNA that enhances anti-tumor immune response in breast cancer by targeting the PD-L1 gene. In patients with breast cancer, downregulation of miR-4759 is associated with poor prognosis.
COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL
(2022)
Article
Oncology
Yo-Liang Lai, Chia-Hsin Liu, Shu-Chi Wang, Shu-Pin Huang, Yi-Chun Cho, Bo-Ying Bao, Chia-Cheng Su, Hsin-Chih Yeh, Cheng-Hsueh Lee, Pai-Chi Teng, Chih-Pin Chuu, Deng-Neng Chen, Chia-Yang Li, Wei-Chung Cheng
Summary: This study identified an eight-gene signature that can predict the prognosis of prostate cancer patients and regulate the steroid hormone pathway. These gene signatures may serve as potential targets for developing novel treatments for castration-resistant prostate cancer.
Article
Oncology
Chaang-Ray Chen, Rong-Shing Chang, Chi-Shuo Chen
Summary: This study identified four stiffness-dependent genes highly associated with poor prognosis in glioma patients through bioinformatics analysis. A pathophysiology-inspired approach revealed the link between brain tumor stiffness and prognosis in glioma patients.
Article
Biochemistry & Molecular Biology
Chia-Hsin Liu, Yo-Liang Lai, Pei-Chun Shen, Hsiu-Cheng Liu, Meng-Hsin Tsai, Yu-De Wang, Wen-Jen Lin, Fang-Hsin Chen, Chia-Yang Li, Shu-Chi Wang, Mien-Chie Hung, Wei-Chung Cheng
Summary: Advancements in high-throughput technology have allowed researchers to obtain a vast amount of multi-omics data in cancer biology. However, traditional statistical models and databases are not sufficient to interpret these data. To address this issue, we present an updated version of the DriverDB cancer driver gene database, called DriverDBv4, which includes more samples, proteomics data, multiple multi-omics algorithms, and new visualization features and customized analysis functions.
NUCLEIC ACIDS RESEARCH
(2023)
Article
Biochemistry & Molecular Biology
Yu-Sen Lin, Ting-Ting Kuo, Chia-Chien Lo, Wei-Chung Cheng, Wei-Chao Chang, Guan-Chin Tseng, Shih-Ting Bai, Yu-Kai Huang, Chih-Ying Hsieh, Han-Shui Hsu, Yi-Fan Jiang, Chen-Yuan Lin, Liang-Chuan Lai, Xing-Guo Li, Yuh-Pyng Sher
Summary: Hypoxia and angiogenesis are key factors in the pathogenesis of esophageal squamous cell carcinoma (ESCC). This study reveals a novel function of ADAM9 in ESCC progression through transcriptional regulation of the angiogenesis pathway. ADAM9 acts as a transcriptional repressor in the nucleus, promoting tumor angiogenesis.
INTERNATIONAL JOURNAL OF BIOLOGICAL SCIENCES
(2021)
Article
Biochemistry & Molecular Biology
Jeffrey Yung-chuan Chao, Hsin-Chuan Chang, Jeng-Kai Jiang, Chih-Yung Yang, Fang-Hsin Chen, Yo-Liang Lai, Wen -Jen Lin, Chia-Yang Li, Shu-Chi Wang, Muh-Hwa Yang, Yu-Feng Lin, Wei-Chung Cheng
Summary: This study identified CRC driver genes and prognostic genes through bioinformatics analysis of sequencing profiles and verified their presence in Taiwanese CRC patients, showing potential for early cancer detection and prognosis assessment.
COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL
(2021)
Article
Medicine, Research & Experimental
Wei-Chung Cheng, Chun-Yu Chang, Chia-Chien Lo, Chih-Ying Hsieh, Ting-Ting Kuo, Guan-Chin Tseng, Sze-Ching Wong, Shu-Fen Chiang, Kevin Chih-Yang Huang, Liang-Chuan Lai, Tzu-Pin Lu, K. S. Clifford Chao, Yuh-Pyng Sher
Summary: The study identified four genes that could serve both therapeutic and diagnostic purposes in stratifying high-risk early-stage LUAD patients for relapse/metastasis. Knockdown of these genes suppressed cancer cell proliferation and migration in vitro and prolonged survival in metastatic tumor mouse models, highlighting their potential as theranostic biomarkers.
Article
Biology
Seyyed Bahram Borgheai, Alyssa Hillary Zisk, John McLinden, James Mcintyre, Reza Sadjadi, Yalda Shahriari
Summary: This study proposed a novel personalized scheme using fNIRS and EEG as the main tools to predict and compensate for the variability in BCI systems, especially for individuals with severe motor deficits. By establishing predictive models, it was found that there were significant associations between the predicted performances and the actual performances.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Hongliang Guo, Hanbo Liu, Ahong Zhu, Mingyang Li, Helong Yu, Yun Zhu, Xiaoxiao Chen, Yujia Xu, Lianxing Gao, Qiongying Zhang, Yangping Shentu
Summary: In this paper, a BDSMA-based image segmentation method is proposed, which improves the limitations of the original algorithm by combining SMA with DE and introducing a cooperative mixing model. The experimental results demonstrate the superiority of this method in terms of convergence speed and precision compared to other methods, and its successful application to brain tumor medical images.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Jingfei Hu, Linwei Qiu, Hua Wang, Jicong Zhang
Summary: This study proposes a novel semi-supervised point consistency network (SPC-Net) for retinal artery/vein (A/V) classification, addressing the challenges of specific tubular structures and limited well-labeled data in CNN-based approaches. The SPC-Net combines an AVC module and an MPC module, and introduces point set representations and consistency regularization to improve the accuracy of A/V classification.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Omair Ali, Muhammad Saif-ur-Rehman, Tobias Glasmachers, Ioannis Iossifidis, Christian Klaes
Summary: This study introduces a novel hybrid model called ConTraNet, which combines the strengths of CNN and Transformer neural networks, and achieves significant improvement in classification performance with limited training data.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Juan Antonio Valera-Calero, Dario Lopez-Zanoni, Sandra Sanchez-Jorge, Cesar Fernandez-de-las-Penas, Marcos Jose Navarro-Santana, Sofia Olivia Calvo-Moreno, Gustavo Plaza-Manzano
Summary: This study developed an easy-to-use application for assessing the diagnostic accuracy of digital pain drawings (PDs) compared to the classic paper-and-pencil method. The results demonstrated that digital PDs have higher reliability and accuracy compared to paper-and-pencil PDs, and there were no significant differences in assessing pain extent between the two methods. The PAIN EXTENT app showed good convergent validity.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Biao Qu, Jialue Zhang, Taishan Kang, Jianzhong Lin, Meijin Lin, Huajun She, Qingxia Wu, Meiyun Wang, Gaofeng Zheng
Summary: This study proposes a deep unrolled neural network, pFISTA-DR, for radial MRI image reconstruction, which successfully preserves image details using a preprocessing module, learnable convolution filters, and adaptive threshold.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Alireza Rafiei, Milad Ghiasi Rad, Andrea Sikora, Rishikesan Kamaleswaran
Summary: This study aimed to improve machine learning model prediction of fluid overload by integrating synthetic data, which could be translated to other clinical outcomes.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Jinlian Ma, Dexing Kong, Fa Wu, Lingyun Bao, Jing Yuan, Yusheng Liu
Summary: In this study, a new method based on MDenseNet is proposed for automatic segmentation of nodular lesions from ultrasound images. Experimental results demonstrate that the proposed method can accurately extract multiple nodules from thyroid and breast ultrasound images, with good accuracy and reproducibility, and it shows great potential in other clinical segmentation tasks.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Jiabao Sheng, SaiKit Lam, Jiang Zhang, Yuanpeng Zhang, Jing Cai
Summary: Omics fusion is an important preprocessing approach in medical image processing that assists in various studies. This study aims to develop a fusion methodology for predicting distant metastasis in nasopharyngeal carcinoma by mitigating the disparities in omics data and utilizing a label-softening technique and a multi-kernel-based neural network.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Zhenxiang Xiao, Liang He, Boyu Zhao, Mingxin Jiang, Wei Mao, Yuzhong Chen, Tuo Zhang, Xintao Hu, Tianming Liu, Xi Jiang
Summary: This study systematically investigates the functional connectivity characteristics between gyri and sulci in the human brain under naturalistic stimulus, and identifies unique features in these connections. This research provides novel insights into the functional brain mechanism under naturalistic stimulus and lays a solid foundation for accurately mapping the brain anatomy-function relationship.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Qianqian Wang, Mingyu Zhang, Aohan Li, Xiaojun Yao, Yingqing Chen
Summary: The development of PARP-1 inhibitors is crucial for the treatment of various cancers. This study investigates the structural regulation of PARP-1 by different allosteric inhibitors, revealing the basis of allosteric inhibition and providing guidance for the discovery of more innovative PARP-1 inhibitors.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Qing Xu, Wenting Duan
Summary: In this paper, a dual attention supervised module, named DualAttNet, is proposed for multi-label lesion detection in chest radiographs. By efficiently fusing global and local lesion classification information, the module is able to recognize targets with different sizes. Experimental results show that DualAttNet outperforms baselines in terms of mAP and AP50 with different detection architectures.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Kaja Gutowska, Piotr Formanowicz
Summary: The primary aim of this research is to propose algorithms for identifying significant reactions and subprocesses within biological system models constructed using classical Petri nets. These solutions enable two analysis methods: importance analysis for identifying critical individual reactions to the model's functionality and occurrence analysis for finding essential subprocesses. The utility of these methods has been demonstrated through analyses of an example model related to the DNA damage response mechanism. It should be noted that these proposed analyses can be applied to any biological phenomenon represented using the Petri net formalism. The presented analysis methods extend classical Petri net-based analyses, enhancing our comprehension of the investigated biological phenomena and aiding in the identification of potential molecular targets for drugs.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Hansle Gwon, Imjin Ahn, Yunha Kim, Hee Jun Kang, Hyeram Seo, Heejung Choi, Ha Na Cho, Minkyoung Kim, Jiye Han, Gaeun Kee, Seohyun Park, Kye Hwa Lee, Tae Joon Jun, Young-Hak Kim
Summary: Electronic medical records have potential in advancing healthcare technologies, but privacy issues hinder their full utilization. Deep learning-based generative models can mitigate this problem by creating synthetic data similar to real patient data. However, the risk of data leakage due to malicious attacks poses a challenge to traditional generative models. To address this, we propose a method that employs local differential privacy (LDP) to protect the model from attacks and preserve the privacy of training data, while generating medical data with reasonable performance.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)
Article
Biology
Siwei Tao, Zonghan Tian, Ling Bai, Yueshu Xu, Cuifang Kuang, Xu Liu
Summary: This study proposes a transfer learning-based method to address the phase retrieval problem in grating-based X-ray phase contrast imaging. By generating a training dataset and using deep learning techniques, this method improves image quality and can be applied to X-ray 2D and 3D imaging.
COMPUTERS IN BIOLOGY AND MEDICINE
(2024)