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Enhancing pathological complete response prediction in breast cancer: the role of dynamic characterization of DCE-MRI and its association with tumor heterogeneity

Breast cancer research : BCR, 2024-05, Vol.26 (1), p.77-77, Article 77

2024

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Building reliable radiomic models using image perturbation

Scientific reports, 2022-06, Vol.12 (1), p.10035-10035, Article 10035

2022

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Noninvasive imaging signatures of HER2 and HR using ADC in invasive breast cancer: repeatability, reproducibility, and association with pathological complete response to neoadjuvant chemotherapy

Breast cancer research : BCR, 2023-06, Vol.25 (1), p.77-77, Article 77

2023

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Multi-omics to predict acute radiation esophagitis in patients with lung cancer treated with intensity-modulated radiation therapy

European journal of medical research, 2023-03, Vol.28 (1), p.126-126, Article 126

2023

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Lung Subregion Partitioning by Incremental Dose Intervals Improves Omics-Based Prediction for Acute Radiation Pneumonitis in Non-Small-Cell Lung Cancer Patients

Cancers, 2022-10, Vol.14 (19), p.4889

2022

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Function-Wise Dual-Omics analysis for radiation pneumonitis prediction in lung cancer patients

Frontiers in pharmacology, 2022-09, Vol.13, p.971849-971849

2022

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Improving radiomic model reliability using robust features from perturbations for head-and-neck carcinoma

Frontiers in oncology, 2022-10, Vol.12, p.974467-974467

2022

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Multimodal Data Integration to Predict Severe Acute Oral Mucositis of Nasopharyngeal Carcinoma Patients Following Radiation Therapy

Cancers, 2023-03, Vol.15 (7), p.2032

2023

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Multi-Organ Omics-Based Prediction for Adaptive Radiation Therapy Eligibility in Nasopharyngeal Carcinoma Patients Undergoing Concurrent Chemoradiotherapy

Frontiers in oncology, 2022-01, Vol.11, p.792024-792024

2022

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Explainable machine learning via intra-tumoral radiomics feature mapping for patient stratification in adjuvant chemotherapy for locoregionally advanced nasopharyngeal carcinoma

Radiologia medica, 2023-07, Vol.128 (7), p.828-838

2023

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Radiomics analysis of patellofemoral joint improves knee replacement risk prediction: Data from the Multicenter Osteoarthritis Study (MOST)

Osteoarthritis and cartilage open, 2024-06, Vol.6 (2), p.100448-100448, Article 100448

2024

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Radiomics-Based Detection of COVID-19 from Chest X-ray Using Interpretable Soft Label-Driven TSK Fuzzy Classifier

Diagnostics (Basel), 2022-10, Vol.12 (11), p.2613

2022

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Quantitative Spatial Characterization of Lymph Node Tumor for N Stage Improvement of Nasopharyngeal Carcinoma Patients

Cancers, 2022-12, Vol.15 (1), p.230

2022

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MULTI-modal radiomics to predict early treatment response from PSA (prostate specific antigen) decline in prostate cancer patients under stereotactic body radiotherapy in MR-Linac

Journal of radiation research and applied sciences, 2024-06, Vol.17 (2), p.100841, Article 100841

2024

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A review of deep learning-based three-dimensional medical image registration methods

Quantitative imaging in medicine and surgery, 2021-12, Vol.11 (12), p.4895-4916

2021

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Virtual Contrast-Enhanced Magnetic Resonance Images Synthesis for Patients With Nasopharyngeal Carcinoma Using Multimodality-Guided Synergistic Neural Network

International journal of radiation oncology, biology, physics, 2022-03, Vol.112 (4), p.1033-1044

2022

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Respiratory deformation registration in 4D-CT/cone beam CT using deep learning

Quantitative imaging in medicine and surgery, 2021-02, Vol.11 (2), p.737-748

2021

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Integration of an imbalance framework with novel high-generalizable classifiers for radiomics-based distant metastases prediction of advanced nasopharyngeal carcinoma

Knowledge-based systems, 2022-01, Vol.235, p.107649, Article 107649

2022

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Multi‐contrast four‐dimensional magnetic resonance imaging (MC‐4D‐MRI): Development and initial evaluation in liver tumor patients

Medical physics (Lancaster), 2021-12, Vol.48 (12), p.7984-7997

2021

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A dual‐supervised deformation estimation model (DDEM) for constructing ultra‐quality 4D‐MRI based on a commercial low‐quality 4D‐MRI for liver cancer radiation therapy

Medical physics (Lancaster), 2022-05, Vol.49 (5), p.3159-3170

2022

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Radiomic feature repeatability and its impact on prognostic model generalizability: A multi-institutional study on nasopharyngeal carcinoma patients

Radiotherapy and oncology, 2023-06, Vol.183, p.109578-109578, Article 109578

2023

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Respiratory Motion Prediction Based on 4D-CT/CBCT Using Deep Learning

Teng, Xinzhi

2019

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ProQuest

Multi-omics and Multi-VOIs to predict esophageal fistula in esophageal cancer patients treated with radiotherapy

Journal of cancer research and clinical oncology, 2024-01, Vol.150 (2), p.39-39, Article 39

2024

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Advances in MRI‐guided precision radiotherapy

Precision radiation oncology, 2022-03, Vol.6 (1), p.75-84

2022

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Deep learning-based bone suppression in chest radiographs using CT-derived features: a feasibility study

Quantitative imaging in medicine and surgery, 2021-12, Vol.11 (12), p.4807-4819

2021

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Enhancing pathological complete response prediction in breast cancer: the role of dynamic characterization of DCE-MRI and its association with tumor heterogeneity

Building reliable radiomic models using image perturbation

Noninvasive imaging signatures of HER2 and HR using ADC in invasive breast cancer: repeatability, reproducibility, and association with pathological complete response to neoadjuvant chemotherapy

Multi-omics to predict acute radiation esophagitis in patients with lung cancer treated with intensity-modulated radiation therapy

Lung Subregion Partitioning by Incremental Dose Intervals Improves Omics-Based Prediction for Acute Radiation Pneumonitis in Non-Small-Cell Lung Cancer Patients

Function-Wise Dual-Omics analysis for radiation pneumonitis prediction in lung cancer patients

Improving radiomic model reliability using robust features from perturbations for head-and-neck carcinoma

Multimodal Data Integration to Predict Severe Acute Oral Mucositis of Nasopharyngeal Carcinoma Patients Following Radiation Therapy

Multi-Organ Omics-Based Prediction for Adaptive Radiation Therapy Eligibility in Nasopharyngeal Carcinoma Patients Undergoing Concurrent Chemoradiotherapy

Explainable machine learning via intra-tumoral radiomics feature mapping for patient stratification in adjuvant chemotherapy for locoregionally advanced nasopharyngeal carcinoma

Radiomics analysis of patellofemoral joint improves knee replacement risk prediction: Data from the Multicenter Osteoarthritis Study (MOST)

Radiomics-Based Detection of COVID-19 from Chest X-ray Using Interpretable Soft Label-Driven TSK Fuzzy Classifier

Quantitative Spatial Characterization of Lymph Node Tumor for N Stage Improvement of Nasopharyngeal Carcinoma Patients

MULTI-modal radiomics to predict early treatment response from PSA (prostate specific antigen) decline in prostate cancer patients under stereotactic body radiotherapy in MR-Linac

A review of deep learning-based three-dimensional medical image registration methods

Virtual Contrast-Enhanced Magnetic Resonance Images Synthesis for Patients With Nasopharyngeal Carcinoma Using Multimodality-Guided Synergistic Neural Network

Respiratory deformation registration in 4D-CT/cone beam CT using deep learning

Integration of an imbalance framework with novel high-generalizable classifiers for radiomics-based distant metastases prediction of advanced nasopharyngeal carcinoma

Multi‐contrast four‐dimensional magnetic resonance imaging (MC‐4D‐MRI): Development and initial evaluation in liver tumor patients

A dual‐supervised deformation estimation model (DDEM) for constructing ultra‐quality 4D‐MRI based on a commercial low‐quality 4D‐MRI for liver cancer radiation therapy

Radiomic feature repeatability and its impact on prognostic model generalizability: A multi-institutional study on nasopharyngeal carcinoma patients

Respiratory Motion Prediction Based on 4D-CT/CBCT Using Deep Learning

Multi-omics and Multi-VOIs to predict esophageal fistula in esophageal cancer patients treated with radiotherapy

Advances in MRI‐guided precision radiotherapy

Deep learning-based bone suppression in chest radiographs using CT-derived features: a feasibility study

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