A5101509264- Radiomics and Machine Learning in Medical Imaging
- Advanced X-ray and CT Imaging
- Cardiac Imaging and Diagnostics
- Radiation Dose and Imaging
- Advanced MRI Techniques and Applications
- Colorectal Cancer Surgical Treatments
- AI in cancer detection
- MRI in cancer diagnosis
- Innovative Microfluidic and Catalytic Techniques Innovation
- Colorectal Cancer Screening and Detection
- 3D Printing in Biomedical Research
- Glioma Diagnosis and Treatment
- Esophageal Cancer Research and Treatment
- Functional Brain Connectivity Studies
- Prostate Cancer Diagnosis and Treatment
- Lung Cancer Diagnosis and Treatment
- Medical Imaging Techniques and Applications
- Scoliosis diagnosis and treatment
- Organ Transplantation Techniques and Outcomes
- Bone Tumor Diagnosis and Treatments
- Advanced machining processes and optimization
- Intraperitoneal and Appendiceal Malignancies
- Lung Cancer Treatments and Mutations
- Liver physiology and pathology
- Tribology and Wear Analysis
Dalian University
2021-2025
Dalian University of Technology
2021-2025
Nanjing Drum Tower Hospital
2024-2025
Shandong First Medical University
2024
University of Electronic Science and Technology of China
2024
Shandong Provincial Hospital
2024
Southern Medical University
2024
Hangzhou Normal University
2023
Shandong Institute of Automation
2019-2023
Chinese Academy of Sciences
2019-2023
We evaluated the performance of newly proposed radiomics multiparametric MRI (RMM), developed and validated based on a multicenter dataset adopting radiomic strategy, for pretreatment prediction pathologic complete response (pCR) to neoadjuvant chemotherapy (NAC) in breast cancer.A total 586 potentially eligible patients were retrospectively enrolled from four hospitals (primary cohort external validation 1-3). Quantitative imaging features extracted T2-weighted imaging, diffusion-weighted...
Abstract Distant metastasis (DM) is the main cause of treatment failure in locally advanced rectal cancer. Adjuvant chemotherapy usually used for distant control. However, not all patients can benefit from adjuvant chemotherapy, and particularly, some may even get worse outcomes after treatment. We develop validate an MRI-based radiomic signature (RS) prediction DM within a multicenter dataset. The RS proved to be independent prognostic factor as it only demonstrates good accuracy...
The aim of this study was to investigate whether pretherapeutic, multiparametric magnetic resonance imaging (MRI) radiomic features can be used for predicting non-response neoadjuvant therapy in patients with locally advanced rectal cancer (LARC).We retrospectively enrolled 425 LARC [allocated a 3:1 ratio primary (n = 318) or validation 107) cohort] who received before surgery. All underwent T1-weighted, T2-weighted, diffusion-weighted, and contrast-enhanced T1-weighted MRI scans receiving...
Accurate predictions of distant metastasis (DM) in locally advanced rectal cancer (LARC) patients receiving neoadjuvant chemoradiotherapy (nCRT) are helpful developing appropriate treatment plans. This study aimed to perform DM prediction through deep learning radiomics.We retrospectively sampled 235 nCRT with the minimum 36 months' postoperative follow-up from three hospitals. Through transfer learning, a radiomic signature (DLRS) based on multiparametric magnetic resonance imaging (MRI)...
<h3>Importance</h3> Accurate identification of lymph node metastasis preoperatively and noninvasively in patients with cervical cancer can avoid unnecessary surgical intervention benefit treatment planning. <h3>Objective</h3> To develop a deep learning model using preoperative magnetic resonance imaging for prediction cancer. <h3>Design, Setting, Participants</h3> This diagnostic study developed an end-to-end to identify (MRI). A total 894 stage IB IIB who underwent radical hysterectomy...
Abstract Objective Temporal lobe epilepsy is a common form of that might be amenable to surgery. However, magnetic resonance imaging (MRI)‐negative hippocampal sclerosis (HS) can hamper early diagnosis and surgical intervention for patients in clinical practice, resulting disease progression. Our aim was automatically detect evaluate the structural alterations HS. Methods Eighty with pharmacoresistant histologically proven HS 80 healthy controls were included study. Two automated classifiers...
The aim of this study was to develop and validate a method disease classification for bipolar disorder (BD) by functional activity connectivity using radiomics analysis. Ninety patients with unmedicated BD II as well 117 healthy controls underwent resting-state magnetic resonance imaging (rs-fMRI). A total 4 types 7018 features were extracted after preprocessing, including mean regional homogeneity (mReHo), amplitude low-frequency fluctuation (mALFF), (RSFC), voxel-mirrored homotopic (VMHC)....
Abstract Background The aim of this work is to combine radiological and pathological information tumor develop a signature for pretreatment prediction discrepancies response at several centers restage patients with locally advanced rectal cancer (LARC) individualized treatment planning. Patients Methods A total 981 consecutive evaluation according regression grade (TRG) who received nCRT were retrospectively recruited from four hospitals (primary cohort external validation 1–3); both...
Background and Purpose: Lymph node status is a key factor for the recommendation of organ preservation patients with locally advanced rectal cancer (LARC) following neoadjuvant therapy but generally confirmed post-operation. This study aimed to preoperatively predict lymph using multiparametric magnetic resonance imaging (MRI)-based radiomic signature. Materials Methods: A total 391 LARC who underwent TME were included, which 261 130 allocated primary cohort validation cohort, respectively....
To develop and validate a pretreatment computed tomography (CT)-based deep-learning (DL) model for predicting the treatment response to concurrent chemoradiation therapy (CCRT) among patients with locally advanced thoracic esophageal squamous cell carcinoma (TESCC).We conducted prospective, multicenter study on therapeutic efficacy of CCRT TESCC across 9 hospitals in China (ChiCTR2000039279). A total 306 diagnosed by histopathology from August 2015 May 2020 were included this study....
Biochemical recurrence (BCR) occurs in up to 27% of patients after radical prostatectomy (RP) and often compromises oncologic survival. To determine whether imaging signatures on clinical prostate magnetic resonance (MRI) could noninvasively characterize biochemical optimize treatment. We retrospectively enrolled 485 underwent RP from 2010 2017 three institutions. Quantitative interpretable features were extracted T2 delineated tumors. Deep learning-based survival analysis was then applied...
Abstract In edge trimming of fiber reinforced plastic composites (FRPs), the friction couple consisting cemented carbide tool and FRP undergoes continuous relative sliding. The tribological properties, represented by wear coefficient, change dynamically with motion distance varying temperature‐force conditions. Its value must be accurately determined to establish a solid foundation for developing advanced models. This paper presents new method mathematically describe such dynamic...
To reduce upgrading and downgrading between needle biopsy (NB) radical prostatectomy (RP) by predicting patient-level Gleason grade groups (GGs) of RP to avoid over- under-treatment.
Abstract Current techniques for the generation of cell-laden microgels are limited by numerous challenges, including poorly uncontrolled batch-to-batch variations, processes that both labor- and time-consuming, high expense devices reagents, low production rates; this hampers translation laboratory findings to clinical applications. To address these we develop a droplet-based microfluidic strategy based on metastable droplet-templating microchannel integration substantial large-scale single...
Encouraging and astonishing developments have recently been achieved in image-based diagnostic technology. Modern medical care imaging technology are becoming increasingly inseparable. However, the current diagnosis pattern of signal to image knowledge inevitably leads information distortion noise introduction procedure reconstruction (from image). Artificial intelligence (AI) technologies that can mine from vast amounts data offer opportunities disrupt established workflows. In this...