Francis Kar-Ho Lee

Privacy-preserving Virtual Contrast-enhanced MRI for Nasopharyngeal Carcinoma: A Multicenter Study

Wen Li, Z Li, Yiming Shi, Saikit Lam et autres

hk, cn, us (code pays fourni par la source)

A Multi-Modal Deep Learning Approach for Predicting Eligibility for Adaptive Radiation Therapy in Nasopharyngeal Carcinoma Patients

Zhichun Li, Zihan Li, Saikit Lam, Xiang Wang et autres

BACKGROUND: Adaptive radiation therapy (ART) can improve prognosis for nasopharyngeal carcinoma (NPC) patients. However, the inter-individual variability in anatomical changes, along with the resulting extension of treatment duration and increased workload for the radiologists, makes the selection of eligible patients a persistent …

hk, cn (code pays fourni par la source)

Weight censorial score: estimation of the weight loss during concurrent chemo-radiotherapy in nasopharyngeal carcinoma patients by image features predicts prognosis

Jiachen Sun, Jiang Zhang, Xinzhi Teng, Francis Kar-Ho Lee et autres

PURPOSE: Bodyweight loss is commonly found in Nasopharyngeal Carcinoma patients during Concurrent Chemo-radiotherapy (CCRT) and has implications for treatment decisions. However, the prognostic value of this weight loss remains uncertain. We addressed it by proposing a novel index Weight Censorial Score (WCS) …

hk, cn (code pays fourni par la source)

Evaluating Virtual Contrast-Enhanced Magnetic Resonance Imaging in Nasopharyngeal Carcinoma Radiation Therapy: A Retrospective Analysis for Primary Gross Tumor Delineation

Wen Li, Dan Zhao, Guangping Zeng, Zhi Chen et autres

hk, cn (code pays fourni par la source)

Pixelwise Gradient Model for Image Fusion (PGMIF): a multi-sequence magnetic resonance imaging (MRI) fusion model for tumor contrast enhancement of nasopharyngeal carcinoma

Ka-Hei Cheng, Wen J. Li, Francis Kar-Ho Lee, Li Tian et autres

Background: Different image modalities capture different aspects of a patient.It is desirable to produce images that capture all such features in a single image.This research investigates the potential of multi-modal image fusion method to enhance magnetic resonance imaging (MRI) tumor contrast and …

hk, cn (code pays fourni par la source)

1496: Image Fusion Using Pixelwise Gradient Model for Image Fusion (PGMIF)

Ka-Hei Cheng, Li Wen, Francis Kar-Ho Lee, Li Tian et autres

2158: A Survival-Driven Radiotherapy Plan Quality Index for Nasopharyngeal Cancer: A Multicenter Study

Jiang Zhang, Xinzhi Teng, Saikit Lam, Zongrui Ma et autres

Pixelwise Gradient Model with GAN for Virtual Contrast Enhancement in MRI Imaging

Ka-Hei Cheng, Wen Li, Francis Kar-Ho Lee, Li Tian et autres

Background: The development of advanced computational models for medical imaging is crucial for improving diagnostic accuracy in healthcare. This paper introduces a novel approach for virtual contrast enhancement (VCE) in magnetic resonance imaging (MRI), particularly focusing on nasopharyngeal cancer (NPC). Methods: The …

hk, cn (code pays fourni par la source)

Model Generalizability Investigation for GFCE-MRI Synthesis in NPC Radiotherapy Using Multi-Institutional Patient-Based Data Normalization

Wen Li, Saikit Lam, Yinghui Wang, Chenyang Liu et autres

Recently, deep learning has been demonstrated to be feasible in eliminating the use of gadoliniumbased contrast agents (GBCAs) through synthesizing gadolinium-free contrast-enhanced MRI (GFCE-MRI) from contrast-free MRI sequences, providing the community with an alternative to get rid of GBCAs-associated safety issues in …

hk, cn (code pays fourni par la source)

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

Xinzhi Teng, Jiang Zhang, Xinyang Han, Jiachen Sun et autres

hk, cn (code pays fourni par la source)

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

Yanjing Dong, Jiang Zhang, Saikit Lam, Xinyu Zhang et autres

(1) Background: Acute oral mucositis is the most common side effect for nasopharyngeal carcinoma patients receiving radiotherapy. Improper or delayed intervention to severe AOM could degrade the quality of life or survival for NPC patients. An effective prediction method for severe AOM …

hk, cn (code pays fourni par la source)

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

Jiang Zhang, Saikit Lam, Xinzhi Teng, Zongrui Ma et autres

BACKGROUND AND PURPOSE: To investigate the radiomic feature (RF) repeatability via perturbation and its impact on cross-institutional prognostic model generalizability in Nasopharyngeal Carcinoma (NPC) patients. MATERIALS AND METHODS: 286 and 183 NPC patients from two institutions were included for model training and …

hk, cn (code pays fourni par la source)