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Πλοήγηση ανά Θέμα "deep learning"

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    • Application of Radiomics and Decision Support Systems for Breast MR Differential Diagnosis 

      Tsougos I., Vamvakas A., Kappas C., Fezoulidis I., Vassiou K. (2018)
      Over the years, MR systems have evolved from imaging modalities to advanced computational systems producing a variety of numerical parameters that can be used for the noninvasive preoperative assessment of breast pathology. ...

    • Artificial Intelligence in Cardiology—A Narrative Review of Current Status 

      Koulaouzidis G., Jadczyk T., Iakovidis D.K., Koulaouzidis A., Bisnaire M., Charisopoulou D. (2022)
      Artificial intelligence (AI) is an integral part of clinical decision support systems (CDSS), offering methods to approximate human reasoning and computationally infer decisions. Such methods are generally based on medical ...

    • Deep learning exploration for SPECT MPI polar map images classification in coronary artery disease 

      Papandrianos N.I., Apostolopoulos I.D., Feleki A., Apostolopoulos D.J., Papageorgiou E.I. (2022)
      Objective: The exploration and the implementation of a deep learning method using a state-of-the-art convolutional neural network for the classification of polar maps represent myocardial perfusion for the detection of ...

    • Deep Learning-Based Automated Diagnosis for Coronary Artery Disease Using SPECT-MPI Images 

      Papandrianos N.I., Feleki A., Papageorgiou E.I., Martini C. (2022)
      (1) Background: Single-photon emission computed tomography (SPECT) myocardial perfusion imaging (MPI) is a long-established estimation methodology for medical diagnosis using image classification illustrating conditions ...

    • Detecting and Locating Gastrointestinal Anomalies Using Deep Learning and Iterative Cluster Unification 

      Iakovidis D.K., Georgakopoulos S.V., Vasilakakis M., Koulaouzidis A., Plagianakos V.P. (2018)
      This paper proposes a novel methodology for automatic detection and localization of gastrointestinal (GI) anomalies in endoscopic video frame sequences. Training is performed with weakly annotated images, using only ...

    • Knee Injury Detection Using Deep Learning on MRI Studies: A Systematic Review 

      Siouras A., Moustakidis S., Giannakidis A., Chalatsis G., Liampas I., Vlychou M., Hantes M., Tasoulis S., Tsaopoulos D. (2022)
      The improved treatment of knee injuries critically relies on having an accurate and costeffective detection. In recent years, deep-learning-based approaches have monopolized knee injury detection in MRI studies. The aim ...

    • Machine learning for rhabdomyosarcoma histopathology 

      Frankel A.O., Lathara M., Shaw C.Y., Wogmon O., Jackson J.M., Clark M.M., Eshraghi N., Keenen S.E., Woods A.D., Purohit R., Ishi Y., Moran N., Eguchi M., Ahmed F.U.A., Khan S., Ioannou M., Perivoliotis K., Li P., Zhou H., Alkhaledi A., Davis E.J., Galipeau D., Randall R.L., Wozniak A., Schoffski P., Lee C.-J., Huang P.H., Jones R.L., Rubin B.P., Darrow M., Srinivasa G., Rudzinski E.R., Chen S., Berlow N.E., Keller C. (2022)
      Correctly diagnosing a rare childhood cancer such as sarcoma can be critical to assigning the correct treatment regimen. With a finite number of pathologists worldwide specializing in pediatric/young adult sarcoma ...

    • Orchard mapping with deep learning semantic segmentation 

      Anagnostis A., Tagarakis A.C., Kateris D., Moysiadis V., Sørensen C.G., Pearson S., Bochtis D. (2021)
      This study aimed to propose an approach for orchard trees segmentation using aerial images based on a deep learning convolutional neural network variant, namely the U-net network. The purpose was the automated detection ...

    • Vertebrae, IVD and spinal canal boundary extraction on MRI, utilizing CT-trained active shape models 

      Liaskos M., Savelonas M.A., Asvestas P.A., Papageorgiou D., Matsopoulos G.K. (2021)
      Purpose: Vertebrae, intervertebral disc (IVD) and spinal canal (SC) displacements are in the root of several spinal cord pathologies. The localization and boundary extraction of these structures, along with the quantification ...

    • Video-Based Eye Blink Identification and Classification 

      Nousias G., Panagiotopoulou E.-K., Delibasis K., Chaliasou A.-M., Tzounakou A.-M., Labiris G. (2022)
      Blink detection and classification can provide a very useful clinical indicator, because of its relation with many neurological and ophthalmological conditions. In this work, we propose a system that automatically detects ...