Yazar "Eren, Furkan" için listeleme
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An Adaptive Feature Extraction Method for Classification of Covid-19 X-Ray Images
Gündoğar, Zeynep; Eren, Furkan (Springer Science and Business Media Deutschland GmbH, 2022)This study aims to detect Covid-19 disease in the fastest and most accurate way from X-ray images by developing a new feature extraction method and deep learning model . Partitioned Tridiagonal Enhanced Multivariance ... -
Ayrıştırım Tabanlı Yöntemler İle Medikal Görüntülerin Sınıflandırılması
Eren, Furkan (Fatih Sultan Mehmet Vakıf Üniversitesi, Lisansüstü Eğitim Enstitüsü, 2021)Bu çalışmada dünya çapında tüm sektörleri etkileyen ve sağlık açısından insan hayatını tehdit eden COVİD-19 virüsünün göğüs X-ışını görüntüleri üzerinden teşhisi problemi ele alınmıştır. Koronavirüs ile enfekte olan ... -
Az Örnekli Öğrenme ile Mikroskobik Görüntülerden Maya Hücresi Segmentasyonu
Alkan, Muhammet; Kiraz, Berna; Eren, Furkan; Uysallı, Yiğit; Kiraz, Alper (IEEE, 2021)Mikroskobik görüntülerden otomatik hücre segmentasyonu, derin sinir ağları veya görüntü işleme teknikleri kullanılarak yapılabilmektedir. Bu tekniklerin ayrı ayrı problemleri ve zorlukları bulunmakla birlikte özellikle ... -
Classification of Covid-19 X-ray Images Using Tridiagonal Matrix Enhanced Multivariance Products Representation (TMEMPR)
Eren, Furkan; Gündoğar,Zeynep (Institute of Electrical and Electronics Engineers Inc., 2021)Medical images are crucial data sources for diseases that can not be diagnosed easily. X-rays, one of the medical images, have high resolution. Processing high-resolution images leads to a few problems such as difficulties ... -
A Deep Learning Model for Automated Segmentation of Fluorescence Cell images
Aydın, Musa; Kiraz, Berna; Eren, Furkan; Uysallı, Yiğit; Morova, Berna; Özcan, Selahattin Can; Acılan, Ceyda; Kiraz, Alper (IOP Publishing Ltd, 2021)Deep learning techniques bring together key advantages in biomedical image segmentation. They speed up the process, increase the reproducibility, and reduce the workload in segmentation and classification. Deep learning ... -
DeepCAN: A Modular Deep Learning System for Automated Cell Counting and Viability Analysis
Eren, Furkan; Aslan, Mete; Kanarya, Dilek; Uysallı, Yigit; Aydin, Musa; Kiraz, Berna; Aydın, Ömer; Kiraz, Alper (IEEE, 2022)Precise and quick monitoring of key cytometric features such as cell count, cell size, cell morphology, and DNA content is crucial for applications in biotechnology, medical sciences, and cell culture research. Traditionally, ... -
Enhancing Resolution and Contrast in Fibre Bundle-Based Fluorescence Microscopy Using Generative Adversarial Network
Ketabchi, Amir Mohammad; Morova, Berna; Uysallı, Yiğit; Aydın, Musa; Eren, Furkan; Bavili, Nima; Pysz, Dariusz; Buczynski, Ryszard; Kiraz, Alper (Wiley, 2024)Fibre bundle (FB)-based endoscopes are indispensable in biology and medical science due to their minimally invasive nature. However, resolution and contrast for fluorescence imaging are limited due to characteristic ...
