Medical Imaging

This cell images dataset is collected using an ultrafast imaging system known as asymmetric-detection time-stretch optical microscopy (ATOM)  for training and evaluation. This novel imaging approach can achieve label-free and high-contrast flow imaging with good cellular resolution images at a very high speed. Each acquired image belongs to one of the four classes: THP1, MCF7, MB231 and PBMC.

  • Biomedical and Health Sciences
  • Last Updated On: 
    Thu, 11/08/2018 - 10:34
    Citation Author(s): 
    Nan Meng, Edmund Lam, Tsia, Kevin Kin Man, So, Hayden Kwok-Hay

    Recent advances in scalp electroencephalography (EEG) as a neuroimaging tool have now allowed researchers to overcome technical challenges and movement restrictions typical in traditional neuroimaging studies.  Fortunately, recent mobile EEG devices have enabled studies involving cognition and motor control in natural environments that require mobility, such as during art perception and production in a museum setting, and during locomotion tasks.

  • Biomedical and Health Sciences
  • Last Updated On: 
    Thu, 11/08/2018 - 10:34
    Citation Author(s): 
    Jesus G. Cruz-Garza, Justin A Brantley, Sho Nakagome, Kim Kontson, Dario Robleto, Jose L. Contreras-Vidal

    Glaucoma is the leading cause of irreversible blindness in the world, and primary angle closure glaucoma (PACG) is one of the main subtypes. PACG patients have narrow chamber angle and can be diagnosed by goniscopy, which may cause discomfort and relies too much on personal experience. Anterior segment OCT is able to provide 3D scan of the anterior chamber and assist the ophthalmologists evaluate the condition of chamber angle. It’s faster and objective compare with goniscopy.

  • Computer Vision
  • Last Updated On: 
    Tue, 07/09/2019 - 09:31

    Welcome to the Retinal Fundus Glaucoma Challenge! REFUGE was organized as a half day Challenge in conjunction with the 5th MICCAI Workshop on Ophthalmic Medical Image Analysis (OMIA), a Satellite Event of the MICCAI 2018 conference in Granada, Spain. The goal of the challenge is to evaluate and compare automated algorithms for glaucoma detection and optic disc/cup segmentation on a common dataset of retinal fundus images. With this challenge, we made available a large dataset of 1200 annotated retinal fundus images.

  • Computer Vision
  • Last Updated On: 
    Tue, 07/09/2019 - 08:57

    Pathologic Myopia Challenge (PALM), as a part of the serial challenge iChallenge, is organized as a half day Challenge, a Satellite Event of the ISBI 2019 conference in Venice, Italy. The PALM challenge focuses on the investigation and development of algorithms associated with the diagnosis of Pathological Myopia (PM) and segmentation of lesions in fundus photos from PM patients. The goal of the challenge is to evaluate and compare automated algorithms for the detection of pathological myopia on a common dataset of retinal fundus images.

  • Computer Vision
  • Last Updated On: 
    Mon, 07/08/2019 - 10:00

    FRAP curve modeling using transient-sensitive analog computer unit with oscilloscopic CRT (Practicum, 2014)

  • Neuroscience
  • Last Updated On: 
    Sat, 07/06/2019 - 07:39

    RECOVERY-FA19 dataset is established for development and evaulation of retinal vessel detection algorithms in fluorescein angiography (FA). RECOVERY-FA19 provides ultra-widefield FA images acquired using Optos California P200DTx camera and labeled binary vessel maps.

  • Standards Research Data
  • Last Updated On: 
    Mon, 06/03/2019 - 15:22

    The provided EEG data were acquired from sixteen healthy young adults (age range 22 - 30 years) with no history of neurological, physical, or psychiatric illness. All the participants were naive BCI users who had not participated in any related experiments before. Informed consents were received from all participants.  The study has been approved by the Institutional Research Ethics Committee of Nazarbayev University.  

     

  • Medical Imaging
  • Last Updated On: 
    Sun, 05/19/2019 - 08:11

    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.

  • Medical Imaging
  • Last Updated On: 
    Fri, 03/29/2019 - 07:00

    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.

  • Medical Imaging
  • Last Updated On: 
    Fri, 03/22/2019 - 10:43

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