Maxillary sinus detection on cone beam computed tomography images using ResNet and Swin Transformer-based UNet.

Objectives: This study, which uses artificial intelligence-based methods, aimed to determine the limits of pathologic conditions and infections related to the maxillary sinus in cone beam computed tomography (CBCT) images to facilitate the work of dentists.

Methods: A new UNet architecture based on a state-of-the-art Swin transformer called Res-Swin-UNet was developed to detect the sinus. The encoder part of the proposed network model consists of a pre-trained ResNet architecture, and the decoder part consists of Swin transformer blocks.

Phytochemical profile, antioxidant, antiproliferative, and enzyme inhibition-docking analyses of Celep & Doğan.

Celep & Doğan is an endemic species of Turkey. To our knowledge, the number of studies on biological activities and phytochemical profiling of this plant is quite limited. Therefore, this study aimed to analyze its activities and phytochemical content in detail.

Efficient COVID-19 Segmentation from CT Slices Exploiting Semantic Segmentation with Integrated Attention Mechanism.

Coronavirus (COVID-19) is a pandemic, which caused suddenly unexplained pneumonia cases and caused a devastating effect on global public health. Computerized tomography (CT) is one of the most effective tools for COVID-19 screening. Since some specific patterns such as bilateral, peripheral, and basal predominant ground-glass opacity, multifocal patchy consolidation, crazy-paving pattern with a peripheral distribution can be observed in CT images and these patterns have been declared as the findings of COVID-19 infection.

Essential Oil and Fatty Acid Composition of Endemic Schreb. from Turkey.

Objectives: species have very high medicinal and commercial importance and contain interesting natural substances. However, there is no report on the essential oil or fatty acid composition of any species. This prompted us to investigate the essential oil and fatty acid composition of Schreb.

Cascaded deep convolutional encoder-decoder neural networks for efficient liver tumor segmentation.

Liver and hepatic tumor segmentation remains a challenging problem in Computer Tomography (CT) images analysis due to its shape variation and vague boundary. The general hypothesis says that deep learning methods produce improved results on medical image segmentation. This paper formulates the segmentation of liver tumor in CT abdominal images as a classification problem, and then solves it using a cascaded classifier framework based on deep convolutional neural networks.

DCCMED-Net: Densely connected and concatenated multi Encoder-Decoder CNNs for retinal vessel extraction from fundus images.

Recent studies have shown that convolutional neural networks (CNNs) can be more accurate, efficient and even deeper on their training if they include direct connections from the layers close to the input to those close to the output in order to transfer activation maps. Through this observation, this study introduces a new CNN model, namely Densely Connected and Concatenated Multi Encoder-Decoder (DCCMED) network. DCCMED contains concatenated multi encoder-decoder CNNs and connects certain layers to the corresponding input of the subsequent encoder-decoder block in a feed-forward fashion, for retinal vessel extraction from fundus image.

Prediction of intrapartum fetal hypoxia considering feature selection algorithms and machine learning models.

Introduction: Cardiotocography (CTG) consists of two biophysical signals that are fetal heart rate (FHR) and uterine contraction (UC). In this research area, the computerized systems are usually utilized to provide more objective and repeatable results.

Materials And Methods: Feature selection algorithms are of great importance regarding the computerized systems to not only reduce the dimension of feature set but also to reveal the most relevant features without losing too much information.

A novel retinal vessel detection approach based on multiple deep convolution neural networks.

Background And Objective: Computer aided detection (CAD) offers an efficient way to assist doctors to interpret fundus images. In a CAD system, retinal vessel (RV) detection is a crucial step to identify the retinal disease regions. However, RV detection is still a challenging problem due to variations in morphology of the vessels on noisy and low contrast fundus images.

Transfer learning based histopathologic image classification for breast cancer detection.

Breast cancer is one of the leading cancer type among women in worldwide. Many breast cancer patients die every year due to the late diagnosis and treatment. Thus, in recent years, early breast cancer detection systems based on patient's imagery are in demand.

Koç & Budak (Caryophyllaceae), a new species from Central Anatolia, Turkey.

A new species was discovered in Hekimhan (Turkey, Malatya province) where it grows on hillsides. The and were compared with each other in terms of their general morphology and seed micromorphology. Description, distribution, illustration and conservation status of the new species are given.

A novel microaneurysms detection approach based on convolutional neural networks with reinforcement sample learning algorithm.

Microaneurysms (MAs) are known as early signs of diabetic-retinopathy which are called red lesions in color fundus images. Detection of MAs in fundus images needs highly skilled physicians or eye angiography. Eye angiography is an invasive and expensive procedure.

In vitro genotoxic effects of four Helichrysum species in human lymphocytes cultures.

Helichrysum sanguineum, Helichrysum pamphylicum, Helichrysum orientale, Helichrysum noeanum (Asteraceae) are medicinal plants. For centuries, they have been used as tea in Turkey because of their medicinal properties. So far no scientific evidence has been found in a literature survey regarding the genotoxic effects of these plants.

Cytogenetic effects of nine Helichrysum taxa in human lymphocytes culture.

Helichrysum Mill. (Asteraceae) species have been used in folk medicine for thousands of years in the world. The in vitro cytogenetic effects in human lymphocytes of nine Helichrysum taxa used in Turkey folk medicine were investigated.