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

Budak, Umit; cibuk, Musa; Comert, Zafer; Sengur, Abdulkadir (Sprınger, 2021)

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 ...

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

Comert, Zafer; Sengur, Abdulkadir; Budak, Umit; Kocamaz, Adnan Fatih (Sprınger, 2019)

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 ...

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

Budak, Umit; Comert, Zafer; Cibuk, Musa; Sengur, Abdulkadir (Churchıll Lıvıngstone, 2020)

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 ...

Efficient approach for digitization of the cardiotocography signals

Comert, Zafer; Sengur, Abdulkadir; Akbulut, Yaman; Budak, Umit; Kocamaz, Adnan Fatih; Bajaj, Varun (Elsevıer, 2020)

Cardiotocography (CTG) is generally provided on printed traces, and digitization of CTG signal is important for forthcoming assessments. In this paper, a new algorithm relies on the box-counting method is offered for the ...

Computer-aided diagnosis system combining FCN and Bi-LSTM model for efficient breast cancer detection from histopathological images

Budak, Umit; Comert, Zafer; Rashid, Zryan Najat; Sengur, Abdulkadir; Cibuk, Musa (Elsevıer, 2019)

Breast cancer (BC) is one of the most frequent types of cancer that adult females suffer from worldwide. Many BC patients face irreversible conditions and even death due to late diagnosis and treatment. Therefore, early ...

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

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

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

Efficient approach for digitization of the cardiotocography signals

Computer-aided diagnosis system combining FCN and Bi-LSTM model for efficient breast cancer detection from histopathological images

Normal and Acute Tympanic Membrane Diagnosis based on Gray Level Co-Occurrence Matrix and Artificial Neural Networks

White Blood Cell Classification Based on Shape and Deep Features

Chronic Tympanic Membrane Diagnosis based on Deep Convolutional Neural Network

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

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

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

Efficient approach for digitization of the cardiotocography signals

Computer-aided diagnosis system combining FCN and Bi-LSTM model for efficient breast cancer detection from histopathological images

Normal and Acute Tympanic Membrane Diagnosis based on Gray Level Co-Occurrence Matrix and Artificial Neural Networks

White Blood Cell Classification Based on Shape and Deep Features

Chronic Tympanic Membrane Diagnosis based on Deep Convolutional Neural Network