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Medical Imaging

The world faces difficulties in terms of eye care, including treatment, quality of prevention, vision rehabilitation services, and scarcity of trained eye care experts. Early detection and diagnosis of ocular pathologies would enable forestall of visual impairment. One challenge that limits the adoption of computer-aided diagnosis tool by ophthalmologists is the number of sight-threatening rare pathologies, such as central retinal artery occlusion or anterior ischemic optic neuropathy, and others are usually ignored.

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This dataset contains 1216 data, which are scanned by HIS-RING PACT system.

the data sampling rate of our system is 40 MSa/s, a 128-elements 2.5MHz full-view ring-shaped transducer with 30mm radius. 

 continuous updating.....

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Diabetic Retinopathy is the second largest cause of blindness in diabetic patients. Early diagnosis or screening can prevent the visual loss. Nowadays , several computer aided algorithms have been developed to detect the early signs of Diabetic Retinopathy ie., Microaneurysms. The AGAR300 dataset presented here facilitate the researchers for benchmarking MA detection algorithms using digital fundus images. Currently, we have released the first set of database which consists of 28 color fundus images, shows the signs of Microaneurysm.

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The dataset is genrated by the fusion of three publicly available datasets: COVID-19 cxr image (https://github.com/ieee8023/covid-chestxray-dataset), Radiological Society of North America (RSNA) (https://www.kaggle.com/c/rsna-pneumonia-detection-challenge), and U.S.  national  library  of  medicine  (USNLM) collected  Montgomery  country - NLM(MC) (https://lhncbc.nlm.nih.gov/publication/pub9931). These datasets were annotated by expert radiologists.

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We chose 8 publicly available CT volumes of COVID-19 positive patients which were available from https://doi.org/10.5281/zenodo.3757476 and used 3D slicer to generate volumetric annotations of 512*512 dimension for 5 lung lobes namely right upper lobe, right middle lobe, right lower lobe, left upper lobe and left lower lobe. These annotations are validated by a radiologist with over 15 years of experience. 

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The data uploaded here shall support the paper 

Decision Tree Analysis of  ...

which has been submitted to IEEE Transactions on Medical Imaging (2020, September 25) by the authors

Julian Mattes, Wolfgang Fenz, Stefan Thumfart, Gerhard Haitchi, Pierre Schmit, Franz A. Fellner

During review the data shall only be visible for the reviewers of this paper. Afterwards this abstract will be modified and complemented and a dataset image will be uploaded.

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