Selected scientific publications on diving medicine and physiology.
2011 Jan 1
A Neuro-fuzzy Approach of Bubble Recognition in Cardiac Video Processing
Chefiri H., Zain J.M.m El-Qawasmeh E., Parlak I.B., Egi S.M., Ademoglu A., Balestra C., Germonpre P., Marroni A., Aydin S.
2D echocardiography which is the golden standard in clinics becomes the new trend of analysis in diving via its high advantages in portability for diagnosis. By the way, the major weakness of this system is non-integrated analysis platform for bubble recognition. In this study, we developed a full automatic method to recognize bubbles in videos. Gabor Wavelet based neural networks are commonly used in face recognition and biometrics. We adopted a similar approach to overcome recognition problem by training our system through real bubble morphologies. Our method does not require a segmentation step which is almost crucial in several studies. Our correct detection rate varies between 82.7-94.3%. After the detection, we classified our findings on ventricles and atria using fuzzy k-means algorithm. Bubbles are clustered in three different subjects with 84.3-93.7% accuracy rates. We suggest that this routine would be useful in longitudinal analysis and subjects with congenital risk factors
There is a limited understanding of the normal function of the pterygoïdeus proprius muscle and the role that this muscle may have in temporomandibular disorders. Despite a well-described anatomical in-vitro approach to this muscle, there are still difficulties in investigating the fossa pterygopalatina. This study reveals an alternative in-vivo approach by magnetic resonance imaging to visualise the muscle in the fossa pterygopalatina on 78 head halves, describe the connections with the musculus temporalis and pterygoïdeus lateralis as well as report the incidence without dealing with the known inconveniences of the dissection approach. The results show an incidence of 12.82% for the musculus pterygoïdeus proprius equally divided between both genders. Two different types of bridging between the musculus temporalis and musculus pterygoïdeus lateralis were also found: (i) 'O' shape (6.41%) and (ii) 'Y' shape (6.41%). This study suggests the use of magnetic resonance imaging to investigate the different connections between vascular and muscular structures in the fossa pterygopalatina. Further research with this approach to link the appearance of the muscle with neurovascular entrapment syndromes is warranted.
Evaluation of critical flicker fusion frequency and perceived fatigue in divers after air and enriched air nitrox diving
Lafère P, Balestra C, Hemelryck W, Donda N, Sakr A, Taher A, Marroni S, Germonpré P.
INTRODUCTION: Many divers report less fatigue following dives breathing enriched air nitrox (EANx) compared with breathing air. A reduction of post-dive fatigue with EANx would suggest a pathological origin, possibly the presence of asymptomatic nitrogen bubbles in the body after a dive.
Automatic bubble detection with neural networks on post decompression frames
Parlak I.B., Egi S.M., Ademoglu A., Balestra C., Germonpre P., Marroni A., Aydin S
Post decompression records in echocardiography are considered to detect micro bubbles and to survey unexplained decompression sickness which is commonly examined by standardized methods such as dive computers and tables. In this study, existent bubbles are detected on transthoracic echicardiografic frames recorded after recreational diving. Bubble detection is performed by Artificial Neural Networks which are trained using bubbles with different morphologies. We showed that bubbles would be detected on four cardiac chambers without image segmentation.
Decompression illness medically reported by hyperbaric treatment facilities: cluster analysis of 1929 cases
Ozyigit T, Egi SM, Denoble P, Balestra C, Aydin S, Vann R, Marroni A.
INTRODUCTION: The term decompression illness (DCI) describes maladies resulting from inadequate decompression, but there is little consensus concerning clinically useful DCI subclasses. Our aim was to explore an objective DCI classification using multivariate statistics to assess naturally associated clusters of DCI manifestations. We also evaluated their mapping onto other DCI classifications and investigated the association with therapeutic outcome.
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