137 datasets

NCL Data2026 · Computed tomography

<h3 dir="ltr">Analysed datasets on body donors (#01–#14)</h3><p dir="ltr">The analyses are based on imaging datasets from fourteen body donors (#01–#14), including MRI- and CT-derived segmentation masks, anatomical markers, and quantitative measurements. The original data can be requested for scientific purposes but are not freely accessible due to data protection and ethical requirements related

figshare + Loughborough Research Repository + GRANTS Data + UP Research Data Repository2026 · Magnetic resonance imaging

<p dir="ltr">This study investigated the location of the dural sac termination (DST) in French bulldogs using magnetic resonance imaging (MRI) and compared the findings with those of other brachycephalic and non-brachycephalic dog breeds. A retrospective review was performed of lumbosacral MRI studies obtained from two veterinary referral institutions between January 2019 and August 2024. The stud

UCL Research Data Repository2026 · Magnetic resonance imaging

<p>Kaplan-Meier survival curves showing DFS in external test cohort 1 <b>(A)</b> and external test cohort 2 <b>(B)</b>. Kaplan–Meier survival curves for OS in external test cohort 1 <b>(C)</b> and external test cohort 2 <b>(D)</b>. Kaplan–Meier survival curves for patients who achieved a pCR <b>(E)</b> and those who did not (non-pCR) <b>(F)</b> after receiving nCRT. AI, artificial intelligence; mr

UCL Research Data Repository2026 · Magnetic resonance imaging

<p>From left to right, the images show the T2WI, manual annotations by radiologists, and segmentation results generated by the AI-mrEMVI model. Color overlays: Red indicates the primary tumor tissue; green indicates intravascular tumor signals; purple indicates dilated vascular structures. AI, artificial intelligence; mr, magnetic resonance; EMVI, extramural vascular invasion; T2WI, T2-weighted im

ZivaHub + Deakin Research Online + DMU Figshare2026 · Magnetic resonance imaging

Insufficient drug accumulation at intracranial tumor sites remains a major obstacle to effective glioma therapy, primarily due to restricted transport across the blood–brain barrier (BBB)/blood–brain tumor barrier (BBTB) and limited active targeting to glioma cells. Here, we report DSPE-based ligand-cross-linked lipid nanoparticles (DBLC LNPs) that integrate lipid-interface engineering, ligand cro

UCL Research Data Repository + HKU DataHub + Swinburne Figshare + DaYta Ya Rona + SUNScholarData + figshare + Loughborough Research Repository + GRANTS Data + UP Research Data Repository2026 · Magnetic resonance imaging

<p>The distributions of demographic and tumor characteristics of rectal cancer patients in two external test cohorts.</p>

UCL Research Data Repository2026 · Magnetic resonance imaging

<p><b>(A)</b> Slice-by-slice manual annotation of multiplanar T2-weighted MR images performed by a radiologist, with annotated regions including the primary tumor (pink), intravascular tumor signals (green), and dilated vascular structures (purple). <b>(B)</b> Model Training and Testing Pipeline. The segmentation training dataset was divided into training and validation subsets at the plane-specif

UCL Research Data Repository2026 · Magnetic resonance imaging

<p>Text A–D, Fig A–O, Table A–F. Text A. Detailed information on the training and external test cohorts. Text B. Data standards. Text C. Detailed training procedure. Text D. Detailed inference procedure. Fig A. Patient enrollment flowchart for the training and external testing of the AI-mrEMVI model. Fig B. Flowchart of MRI marker evaluation. Fig C. Construction of the segmentation training datase

UCL Research Data Repository2026 · Magnetic resonance imaging

<p>The color intensity in the heatmap represents the pairwise Cohen’s kappa values between each pair of readers. R1 and R2 denote junior radiologists (H.H. and Y.Y.); R3 and R4, mid-level radiologists (H.Y. and Y.L.); and R5 and R6, senior radiologists (L.Y. and W.X.). R, reader. AI, artificial intelligence; mr, magnetic resonance; EMVI, extramural vascular invasion.</p>

UCL Research Data Repository2026 · Magnetic resonance imaging

<p><b>(A)</b> Confusion matrix for external test cohort 1. <b>(B)</b> Confusion matrix for external test cohort 2. <b>(C)</b> Classification performance metrics of the model. AI, artificial intelligence; mr, magnetic resonance; EMVI, extramural vascular invasion; T2WI, T2-weighted image; PPV, Positive Predictive Value; NPV, Negative Predictive Value; AUC, Area Under the ROC Curve.</p>

UCL Research Data Repository + HKU DataHub + Swinburne Figshare + DaYta Ya Rona + SUNScholarData + figshare + Loughborough Research Repository + GRANTS Data + UP Research Data Repository2026 · Magnetic resonance imaging

<div><p>MRI-detected extramural vascular invasion (mrEMVI) is an important prognostic biomarker in rectal cancer, reflecting tumor invasiveness and metastatic potential. To address the subjectivity and inter-observer variability inherent in manual mrEMVI assessment, this study trained and validated an nnUNet-based segmentation model for automated voxel-level localization and visualization of mrEMV

ZivaHub + Deakin Research Online + DMU Figshare + HKU DataHub + Swinburne Figshare + DaYta Ya Rona + SUNScholarData + figshare + Loughborough Research Repository + GRANTS Data + UP Research Data Repository2026 · Magnetic resonance imaging

<div><p>Due to the substantial impact of brain tumors on human health, precise identification of tumor types is vital for patient prognosis and guiding treatment decisions. Magnetic Resonance Imaging (MRI) technology, owing to its non-invasive nature and high resolution, is indispensable in accurately classifying brain tumor types. However, manual interpretation of MRI images is not only time-cons

ZivaHub + Deakin Research Online + DMU Figshare2026 · Magnetic resonance imaging

<p>The ROC curve of the proposed model on the Kaggle dataset.</p>

ZivaHub + Deakin Research Online + DMU Figshare + HKU DataHub + Swinburne Figshare + DaYta Ya Rona + SUNScholarData + figshare + Loughborough Research Repository + GRANTS Data + UP Research Data Repository2026 · Magnetic resonance imaging

<p>The performance index of the proposed model on the Chen dataset.</p>

ZivaHub + Deakin Research Online + DMU Figshare + HKU DataHub + Swinburne Figshare + DaYta Ya Rona + SUNScholarData + figshare + Loughborough Research Repository + GRANTS Data + UP Research Data Repository2026 · Magnetic resonance imaging

<p>Detailed metrics values of the proposed model on the Chen dataset.</p>

ZivaHub + Deakin Research Online + DMU Figshare + HKU DataHub + Swinburne Figshare + DaYta Ya Rona + SUNScholarData + figshare + Loughborough Research Repository + GRANTS Data + UP Research Data Repository2026 · Magnetic resonance imaging

<p>Training hyperparameter values for the proposed model.</p>

ZivaHub + Deakin Research Online + DMU Figshare + HKU DataHub + Swinburne Figshare + DaYta Ya Rona + SUNScholarData + figshare + Loughborough Research Repository + GRANTS Data + UP Research Data Repository2026 · Magnetic resonance imaging

<div><p>Due to the substantial impact of brain tumors on human health, precise identification of tumor types is vital for patient prognosis and guiding treatment decisions. Magnetic Resonance Imaging (MRI) technology, owing to its non-invasive nature and high resolution, is indispensable in accurately classifying brain tumor types. However, manual interpretation of MRI images is not only time-cons

ZivaHub + Deakin Research Online + DMU Figshare2026 · Magnetic resonance imaging

<p>The scatter plot of the proposed model on the Chen dataset.</p>

ZivaHub + Deakin Research Online + DMU Figshare + HKU DataHub + Swinburne Figshare + DaYta Ya Rona + SUNScholarData + figshare + Loughborough Research Repository + GRANTS Data + UP Research Data Repository2026 · Magnetic resonance imaging

<p>Parameter details of comparative models on the Chen dataset.</p>

ZivaHub + Deakin Research Online + DMU Figshare + HKU DataHub + Swinburne Figshare + DaYta Ya Rona + SUNScholarData + figshare + Loughborough Research Repository + GRANTS Data + UP Research Data Repository2026 · Magnetic resonance imaging

<p>Performance indicators of the proposed model on the Brain Tumor MRI dataset.</p>

ZivaHub + Deakin Research Online + DMU Figshare + HKU DataHub + Swinburne Figshare + DaYta Ya Rona + SUNScholarData + figshare + Loughborough Research Repository + GRANTS Data + UP Research Data Repository2026 · Magnetic resonance imaging

<p>Performance comparison data of models on Chen dataset with Gaussian noise.</p>

ZivaHub + Deakin Research Online + DMU Figshare + HKU DataHub + Swinburne Figshare + DaYta Ya Rona + SUNScholarData + figshare + Loughborough Research Repository + GRANTS Data + UP Research Data Repository2026 · Magnetic resonance imaging

<p>Comparison of our proposed model with previous models.</p>

ZivaHub + Deakin Research Online + DMU Figshare2026 · Magnetic resonance imaging

<p>The ROC curve of the proposed model on the Chen dataset.</p>

ZivaHub + Deakin Research Online + DMU Figshare2026 · Magnetic resonance imaging

<div><p>Due to the substantial impact of brain tumors on human health, precise identification of tumor types is vital for patient prognosis and guiding treatment decisions. Magnetic Resonance Imaging (MRI) technology, owing to its non-invasive nature and high resolution, is indispensable in accurately classifying brain tumor types. However, manual interpretation of MRI images is not only time-cons

ZivaHub + Deakin Research Online + DMU Figshare2026 · Magnetic resonance imaging

<p>Framework of the proposed brain tumor classification system.</p>