PubMed İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/397
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Article Citation - WoS: 3Citation - Scopus: 3An FDTD-Based Computer Simulation Platform for Shock Wave Propagation in Electrohydraulic Lithotripsy(Elsevier Ireland Ltd, 2013-06) Yilmaz, Bulent; Çiftçi, EmreExtracorporeal Shock Wave Lithotripsy (ESWL) is based on disintegration of the kidney stone by delivering high-energy shock waves that are created outside the body and transmitted through the skin and body tissues. Nowadays high-energy shock waves are also used in orthopedic operations and investigated to be used in the treatment of myocardial infarction and cancer. Because of these new application areas novel lithotriptor designs are needed for different kinds of treatment strategies. In this study our aim was to develop a versatile computer simulation environment which would give the device designers working on various medical applications that use shock wave principle a substantial amount of flexibility while testing the effects of new parameters such as reflector size, material properties of the medium, water temperature, and different clinical scenarios. For this purpose, we created a finite-difference time-domain (FDTD)-based computational model in which most of the physical system parameters were defined as an input and/or as a variable in the simulations. We constructed a realistic computational model of a commercial electrohydraulic lithotriptor and optimized our simulation program using the results that were obtained by the manufacturer in an experimental setup. We, then, compared the simulation results with the results from an experimental setup in which oxygen level in water was varied. Finally, we studied the effects of changing the input parameters like ellipsoid size and material, temperature change in the wave propagation media, and shock wave source point misalignment. The simulation results were consistent with the experimental results and expected effects of variation in physical parameters of the system. The results of this study encourage further investigation and provide adequate evidence that the numerical modeling of a shock wave therapy system is feasible and can provide a practical means to test novel ideas in new device design procedures. © 2012 Elsevier Ireland Ltd. © 2014 Elsevier B.V., All rights reserved.; MEDLINE® is the source for the MeSH terms of this document.Article Citation - Scopus: 15An Effective Colorectal Polyp Classification for Histopathological Images Based on Supervised Contrastive Learning(Elsevier Ltd, 2024-04) Yengec-Tasdemir, Sena Busra; Aydin, Zafer; Akay, Ebru; Doǧan, Serkan; Yilmaz, BulentEarly detection of colon adenomatous polyps is pivotal in reducing colon cancer risk. In this context, accurately distinguishing between adenomatous polyp subtypes, especially tubular and tubulovillous, from hyperplastic variants is crucial. This study introduces a cutting-edge computer-aided diagnosis system optimized for this task. Our system employs advanced Supervised Contrastive learning to ensure precise classification of colon histopathology images. Significantly, we have integrated the Big Transfer model, which has gained prominence for its exemplary adaptability to visual tasks in medical imaging. Our novel approach discerns between in-class and out-of-class images, thereby elevating its discriminatory power for polyp subtypes. We validated our system using two datasets: a specially curated one and the publicly accessible UniToPatho dataset. The results reveal that our model markedly surpasses traditional deep convolutional neural networks, registering classification accuracies of 87.1% and 70.3% for the custom and UniToPatho datasets, respectively. Such results emphasize the transformative potential of our model in polyp classification endeavors. © 2024 Elsevier B.V., All rights reserved.