no code implementations • 9 Feb 2024 • Muhammad Uzair Zahid, Aysen Degerli, Fahad Sohrab, Serkan Kiranyaz, Tahir Hamid, Rashid Mazhar, Moncef Gabbouj
Early detection of myocardial infarction (MI), a critical condition arising from coronary artery disease (CAD), is vital to prevent further myocardial damage.
no code implementations • 27 Sep 2023 • Ilke Adalioglu, Mete Ahisali, Aysen Degerli, Serkan Kiranyaz, Moncef Gabbouj
Myocardial infarction (MI) is a severe case of coronary artery disease (CAD) and ultimately, its detection is substantial to prevent progressive damage to the myocardium.
no code implementations • 19 Apr 2023 • Aysen Degerli, Pekka Jakala, Juha Pajula, Milla Immonen, Miguel Bordallo Lopez
Stroke is a major cause of mortality and disability worldwide from which one in four people are in danger of incurring in their lifetime.
1 code implementation • 29 Sep 2022 • Mete Ahishali, Aysen Degerli, Serkan Kiranyaz, Tahir Hamid, Rashid Mazhar, Moncef Gabbouj
The proposed restoration approach achieves over 90% F1-Score which is significantly higher than the performance of any deep model.
no code implementations • 14 Apr 2022 • Aysen Degerli, Fahad Sohrab, Serkan Kiranyaz, Moncef Gabbouj
In this study, we propose a framework for early detection of MI over multi-view echocardiography that leverages one-class classification (OCC) techniques.
no code implementations • 21 Feb 2022 • Aysen Degerli, Serkan Kiranyaz, Muhammad E. H. Chowdhury, Moncef Gabbouj
To address the data scarcity encountered in training and especially in evaluation, this study extends the largest COVID-19 CXR dataset: QaTa-COV19 with 121, 378 CXRs including 9258 COVID-19 samples with their corresponding ground-truth segmentation masks that are publicly shared with the research community.
1 code implementation • 9 Nov 2021 • Aysen Degerli, Serkan Kiranyaz, Tahir Hamid, Rashid Mazhar, Moncef Gabbouj
Following the blockage of a coronary artery, the regional wall motion abnormality (RWMA) of the ischemic myocardial segments is the earliest change to set in.
no code implementations • 28 Jan 2021 • Aysen Degerli, Mete Ahishali, Serkan Kiranyaz, Muhammad E. H. Chowdhury, Moncef Gabbouj
To address this need, in this study, we propose a reliable COVID-19 detection network: ReCovNet, which can discriminate COVID-19 pneumonia from 14 different thoracic diseases and healthy subjects.
no code implementations • 5 Oct 2020 • Aysen Degerli, Morteza Zabihi, Serkan Kiranyaz, Tahir Hamid, Rashid Mazhar, Ridha Hamila, Moncef Gabbouj
Myocardial infarction (MI), or commonly known as heart attack, is a life-threatening health problem worldwide from which 32. 4 million people suffer each year.
no code implementations • 26 Sep 2020 • Aysen Degerli, Mete Ahishali, Mehmet Yamac, Serkan Kiranyaz, Muhammad E. H. Chowdhury, Khalid Hameed, Tahir Hamid, Rashid Mazhar, Moncef Gabbouj
To accomplish this, we have compiled the largest dataset with 119, 316 CXR images including 2951 COVID-19 samples, where the annotation of the ground-truth segmentation masks is performed on CXRs by a novel collaborative human-machine approach.
no code implementations • 11 Aug 2020 • Serkan Kiranyaz, Aysen Degerli, Tahir Hamid, Rashid Mazhar, Rayyan Ahmed, Rayaan Abouhasera, Morteza Zabihi, Junaid Malik, Ridha Hamila, Moncef Gabbouj
It further enables medical experts to gain an enhanced visualization capability of echo images through color-coded segments along with their "maximum motion displacement" plots helping them to better assess wall motion and LV Ejection-Fraction (LVEF).
1 code implementation • 7 Jun 2020 • Mete Ahishali, Aysen Degerli, Mehmet Yamac, Serkan Kiranyaz, Muhammad E. H. Chowdhury, Khalid Hameed, Tahir Hamid, Rashid Mazhar, Moncef Gabbouj
The detection of COVID-19 in early stages is not a straightforward task from chest X-ray images according to expert medical doctors because the traces of the infection are visible only when the disease has progressed to a moderate or severe stage.
no code implementations • 8 May 2020 • Mehmet Yamac, Mete Ahishali, Aysen Degerli, Serkan Kiranyaz, Muhammad E. H. Chowdhury, Moncef Gabbouj
Any technological tool that can be provided to healthcare practitioners to save time, effort, and possibly lives has crucial importance.
2 code implementations • 17 May 2019 • Dat Thanh Tran, Mehmet Yamac, Aysen Degerli, Moncef Gabbouj, Alexandros Iosifidis
Compressive Learning is an emerging topic that combines signal acquisition via compressive sensing and machine learning to perform inference tasks directly on a small number of measurements.
no code implementations • 15 Oct 2018 • Aysen Degerli, Sinem Aslan, Mehmet Yamac, Bulent Sankur, Moncef Gabbouj
Recent literature works show that compressive image classification is possible in CS domain without reconstruction of the signal.