The EEG data were acquired from 16 healthy young adults (age range 22 - 30 years) with no neurological, physical, or psychiatric illness history. All the participants were naive BCI users who had not participated in any related experiments before. Informed consent was received from all participants.   

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2919 Views

We present the first approach to automatically detect and track a needle in an endoscopic ultrasound (EUS) video. EUS is a fundamental medical procedure that is used extensively for biopsying targets in the upper gastro-intestinal tract. The approach enables various new applications for advancing EUS, including automatic EUS workflow analysis, automatic report generation, video summarization, technical skills assessment and quality indicator automation. Our approach does not require annotations of needles in videos, which is a laborious and demanding task.

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128 Views

The dataset contains 208 patient scans that spread over three parts of anatomy(head, neck, and pelvis). The dataset aims to establish accurate anatomical correspondences between MegaVoltage Planar Digital Radio-graphs (MV-DRs) andKiloVoltage Digital Reconstructed Radiographs (KV-DRRs), which are widely used in Image-Guided Radiation Therapy (IGRT) to verify patients’ positions for accurate radiotherapy delivery.

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97 Views

This study investigated possible long-term cardiotoxicity-related left-ventricular (LV) contractile dysfunction in breast cancer patients who had treatment with anti-neoplastic chemotherapy agents (CTA). An automated cardiac contractility analysis tool consisting of quantization-based boundary detection and meshfree Radial Point Interpolation Method-based numerical analysis measured torsion and 3D strains for comparisons to healthy subjects to investigate LV remodeling otherwise not indicated by LV ejection fraction (LVEF).

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60 Views

Dataset for journal manuscript titled: 'Cardiac Motion Estimation from Noisy Medical Images: A Regularisation Framework Applied on Pairwise Image Registration Displacement Fields'

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123 Views

The DualModal2019 is a dual-modal fundus image dataset. It is for vessel, arteriole, and venule segmentation tasks. The dataset consists of five types of images: RGB color images, the 570 nm and 610 nm monochromic images, and the corresponding manually annotated ground truth images of the arterioles and venules.

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702 Views

This dataset collection contains eleven datasets used in Locally Linear Embedding and fMRI feature selection in psychiatric classification.

The datasets given in the Links section are reduced subsets of those contained in their respective tar files (a consequence of Mendeley Data's 10GB limitation).

The Linked datasets (not the tar files) contain just the MATLAB file and the resting state image (or block-design fMRI for the MRN dataset), where appropriate.

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470 Views

This raw data was used in a study looking at the correlations between 10 image quality metrics (IQMs) and the subjective image quality scores of expert radiologists. Nine MR images of the abdomin and of the brain were retrospectively degraded by noise, motion, undersampling, compression, and blurring. Each of these images we then evaluated by the radiologists and the IQM scores were calculated. This data set is made up of the radiologists' scores and the IQM scores.

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153 Views

Changes in left ventricular (LV) aggregate cardiomyocyte  orientation and deformation underlie cardiac function and dysfunction. As such, in vivo aggregate cardiomyocyte "myofiber" strain has mechanistic significance, but currently there exists no established technique to measure in vivo cardiomyocyte strain.

 

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319 Views

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