Deep learning for cardiac image segmentation: A review

Deep learning has become the most widely used approach for cardiac image segmentation in recent years. In this paper, we provide a review of over 100 cardiac image segmentation papers using deep learning, which covers common imaging modalities including magnetic resonance imaging (MRI), computed tomography (CT), and ultrasound (US) and major anatomical structures of interest (ventricles, atria and vessels). In addition, a summary of publicly available cardiac image datasets and code repositories are included to provide a base for encouraging reproducible research. Finally, we discuss the challenges and limitations with current deep learning-based approaches (scarcity of labels, model generalizability across different domains, interpretability) and suggest potential directions for future research

Advances in Digital Processing of Low-Amplitude Components of Electrocardiosignals

This manual has been published within the framework of the BME-ENA project under the responsibility of National Technical University of Ukraine. The BME-ENA “Biomedical Engineering Education Tempus Initiative in Eastern Neighbouring Area”, Project Number: 543904-TEMPUS-1-2013-1-GR-TEMPUS-JPCR is a Joint Project within the TEMPUS IV program. This project has been funded with support from the European Commission.Навчальний посібник присвячено розробці методів та засобів для неінвазивного виявлення та дослідження тонких проявів електричної активності серця. Особлива увага приділяється вдосконаленню інформаційного та алгоритмічного забезпечення систем електрокардіографії високого розрізнення для ранньої діагностики електричної нестабільності міокарда, а також для оцінки функціонального стану плоду під час вагітності. Теоретичні основи супроводжуються прикладами реалізації алгоритмів за допомогою системи MATLAB. Навчальний посібник призначений для студентів, аспірантів, а також фахівців у галузі біомедичної електроніки та медичних працівників.The teaching book is devoted to development and research of methods and tools for non-invasive detection of subtle manifistations of heart electrical activity. Particular attention is paid to the improvement of information and algorithmic support of high resolution electrocardiography for early diagnosis of myocardial electrical instability, as well as for the evaluation of the functional state of the fetus during pregnancy examination. The theoretical basis accompanied by the examples of implementation of the discussed algorithms with the help of MATLAB. The teaching book is intended for students, graduate students, as well as specialists in the field of biomedical electronics and medical professionals

Deep Learning in Cardiology

The medical field is creating large amount of data that physicians are unable to decipher and use efficiently. Moreover, rule-based expert systems are inefficient in solving complicated medical tasks or for creating insights using big data. Deep learning has emerged as a more accurate and effective technology in a wide range of medical problems such as diagnosis, prediction and intervention. Deep learning is a representation learning method that consists of layers that transform the data non-linearly, thus, revealing hierarchical relationships and structures. In this review we survey deep learning application papers that use structured data, signal and imaging modalities from cardiology. We discuss the advantages and limitations of applying deep learning in cardiology that also apply in medicine in general, while proposing certain directions as the most viable for clinical use.Comment: 27 pages, 2 figures, 10 table

Experimental studies on coronary perfusion with pump-oxygenator

1. Methods of retrograde coronary perfusion and direct coronary artery perfusion in combination with a bubble oxygenator were investigated in dogs. 2. Ventricular fibrillation occurred more frequently during the operation in hypothermia than in the operation performed in combination with the extracorporeal circulation. 3. The optimal pressure of perfusion is considered to be 30 to 35 mm Hg in retroperfusion, whereas, 100 mm Hg in direct coronary artery perfusion. 4. Perfusion by the pressure bottle method is preferable to the gravity method because the fall of blood temperature in the irrigation tubing might cause ventricular fibrillation. 5. From the metabolic study of the methods is clear that there is a tendency to myocardial anoxia after 15 to 20 minutes of perfusion in both methods.</p

Studies of the effects of gravitational and inertial forces on cardiovascular and respiratory dynamics

The current status and application are described of the biplane video roentgen densitometry, videometry and video digitization systems. These techniques were developed, and continue to be developed for studies of the effects of gravitational and inertial forces on cardiovascular and respiratory dynamics in intact animals and man. Progress is reported in the field of lung dynamics and three-dimensional reconstruction of the dynamic thoracic contents from roentgen video images. It is anticipated that these data will provide added insight into the role of shape and internal spatial relationships (which is altered particularly by acceleration and position of the body) of these organs as an indication of their functional status

Pitx2c is reactivated in the failing myocardium and stimulates Myf5 expression in cultured cardiomyocytes

[Abstract] Background. Pitx2 (paired-like homeodomain 2 transcription factor) is crucial for heart development, but its role in heart failure (HF) remains uncertain. The present study lays the groundwork implicating Pitx2 signalling in different modalities of HF. Methodology/Principal Findings. A variety of molecular, cell-based, biochemical, and immunochemical assays were used to evaluate: (1) Pitx2c expression in the porcine model of diastolic HF (DHF) and in patients with systolic HF (SHF) due to dilated and ischemic cardiomyopathy, and (2) molecular consequences of Pitx2c expression manipulation in cardiomyocytes in vitro. In pigs, the expression of Pitx2c, physiologically downregulated in the postnatal heart, is significantly re-activated in left ventricular (LV) failing myocardium which, in turn, is associated with increased expression of a restrictive set of Pitx2 target genes. Among these, Myf5 was identified as the top upregulated gene. In vitro, forced expression of Pitx2c in cardiomyocytes, but not in skeletal myoblasts, activates Myf5 in dose-dependent manner. In addition, we demonstrate that the level of Pitx2c is upregulated in the LV-myocardium of SHF patients. Conclusions/Significance. The results provide previously unrecognized evidence that Pitx2c is similarly reactivated in postnatal/adult heart at distinct HF phenotypes and suggest that Pitx2c is involved, directly or indirectly, in the regulation of Myf5 expression in cardiomyocytes.Galicia. Consellería de Cultura, Educación e Ordenación Universitaria; GRC 2013/061Andalucía. Junta. Consejería de Innovación, Ciencia y Empresa; CTS1416Centro Nacional de Investigaciones Cardiovasculares Carlos III; CNIC-T 2009/0