WoS İndeksli Yayınlar Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/394

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2016 - 20172

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Has files: YesPublisher: search.filters.publisher.SPIE - The International Society for Optics and Photonics

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  • Conference Object
    Citation - Scopus: 3
    Mixture of Learners for Cancer Stem Cell Detection Using Cd13 and H&E Stained Images
    (SPIE - The International Society for Optics and Photonics, 2016-03-23) Oguz, Oguzhan; Akbas, Cem Emre; Mallah, Maen; Tasdemir, Kasim; Guzelcan, Ece Akhan; Muenzenmayer, Christian; Atalay, Rengul Cetin; Akhan Güzelcan, Ece; Tagdemir, Kaslm
    In this article, algorithms for cancer stem cell (CSC) detection in liver cancer tissue images are developed. Conventionally, a pathologist examines of cancer cell morphologies under microscope. Computer aided diagnosis systems (CAD) aims to help pathologists in this tedious and repetitive work. The first algorithm locates CSCs in CD13 stained liver tissue images. The method has also an online learning algorithm to improve the accuracy of detection. The second family of algorithms classify the cancer tissues stained with H&E which is clinically routine and cost effective than immunohistochemistry (IHC) procedure. The algorithms utilize 1D-SIFT and eigen-analysis based feature sets as descriptors. Normal and cancerous tissues can be classified with 92.1% accuracy in H&E stained images. Classification accuracy of low and high-grade cancerous tissue images is 70.4%. Therefore, this study paves the way for diagnosing the cancerous tissue and grading the level of it using HSLE stained microscopic tissue images.
  • Conference Object
    Finding Glenoid Surface on Scapula in 3D Medical Images for Shoulder Joint Implant Operation Planning-3D OCR
    (SPIE - The International Society for Optics and Photonics, 2017-03-17) Sadeghi, Majid Mohammad; Kececi, Emin Faruk; Bilsel, Kerem; Aralasmak, Ayse; Mohammad Sadeghi, Majid
    Medical imaging has great importance in earlier detection, better treatment and follow-up of diseases. 3D Medical image analysis with CT Scan and MRI images has also been used to aid surgeries by enabling patient specific implant fabrication, where having a precise three dimensional model of associated body parts is essential. In this paper, a 3D image processing methodology for finding the plane on which the glenoid surface has a maximum surface area is proposed. Finding this surface is the first step in designing patient specific shoulder joint implant.