Medical Imaging

This dataset contains 91 computed tomography pulmonary angiograms positive for pulmonary embolism. At least one experience radiologist has segmented all clots in each of the scans. The dataset was originated for the ISBI challenge cad-pe.

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  • Medical Imaging
  • Last Updated On: 
    Thu, 10/17/2019 - 10:25

    The purpose of this challenge is to provide standardization of methods for assessing and benchmarking deep learning approaches to ultrasound image formation from ultrasound channel data that will live beyond the challenge.

  • Artificial Intelligence
  • Machine Learning
  • Medical Imaging
  • Signal Processing
  • Last Updated On: 
    Mon, 12/09/2019 - 15:02

    基于波动算法的快速视网膜分割

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    光电成像与测量技术实验室

    地址:中国天津市卫经路92号

    邮政编码:300072

    电话:+ 86-22-27404535传真:+ 86-22-27404535

    团队网站:http : //jyxy.tju.edu.cn/Precision/PEIT_1/index.html

    87 views
  • Image Processing
  • Last Updated On: 
    Sun, 01/12/2020 - 07:53

    Hyperspectral (HS) imaging presents itself as a non-contact, non-ionizing and non-invasive technique, proven to be suitable for medical diagnosis. However, the volume of information contained in these images makes difficult providing the surgeon with information about the boundaries in real-time. To that end, High-Performance-Computing (HPC) platforms become necessary. This paper presents a comparison between the performances provided by five different HPC platforms while processing a spatial-spectral approach to classify HS images, assessing their main benefits and drawbacks.

    406 views
  • Image Processing
  • Last Updated On: 
    Thu, 08/29/2019 - 05:30

    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.

    225 views
  • 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.

    492 views
  • 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.

    362 views
  • Computer Vision
  • Last Updated On: 
    Thu, 07/18/2019 - 23:43

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

    15 views
  • 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.

    251 views
  • 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.  

     

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

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