Lung region segmentation based on computer tomographic images

The article is written for the benefit of hospitals in order to identify segments of the lungs and thereby help in the process of bisecting lungs according to their respective segments during surgery. Further research in this area can also help in identification of various abnormalities related to each segment and also identify abnormal walls of unhealthy lungs. Segmentation of the lungs has not been implemented in reality, as the lung, being an organ with dynamic chest volumes during respiratory cycles, makes it impossible to address changes during respiration unlike fixed structures like the brain. Further, abnormalities situated on the walls of lung segments, make it more difficult to address volume changes concerned with the lungs. The author of this paper has provided a more effective method to identify various lung segments by using various well known segmentation techniques combined together to identify moving lung image segments more effectively

Detection of fibrosis regions in the lungs based on CT scans

The main aim in the article was to provide an accurate, simple and fast algorithm that can increase the performance of the system and thereby the efficiency. Accurate results for lung images have not been accurate as the edges form in many diverse ways. Thereby, a universally applicable edge detection algorithm cannot comply with the purpose of detecting fibrosis. Thus by considering and furthermore introducing a deep convolutional neural network with pixel manipulation, the detection of fibrosis can be made easy, efficient and even accurate unlike the traditional learning structures. By implementing this we are free from extraction of features or even computation of multiple channels and thus suggesting a very straight forward method in terms of the detection and output accuracy

Bilateral breast reduction surgery at Mater Dei Hospital : analysis of physical and psychological symptoms using the BREAST-Q

Introduction: The literature describes the high patient satisfaction rate after breast reduction. In this retrospective study, we use the BREAST-Q to analyse satisfaction with breast appearance and physical, psychosocial and sexual well-being of patients who underwent bilateral breast reduction (BBR) at Mater Dei Hospital (MDH). We also looked into whether age, co-morbidities and weight of breast tissue removed makes a difference to the overall satisfaction rate. Method: Permission to use the BREAST-Q questionnaire and translate it into Maltese was obtained from Mapi Reasearch Trust. The questionnaire was offered either in Maltese or in English, after an official translation was produced following a linguistic validation process. All patients who underwent BBR at MDH under the care of both consultant Plastic Surgeons were invited to complete the BREAST-Q questionnaire via a telephone call and asked to come to MDH to fill it in. Other patient specific information was obtained from their hospital notes. Results: We hope to demonstrate a better quality of life following surgery and aim to compare the results of this study to others carried out worldwide. In this way we can better understand the local situation and see where there is the room for improvement. Conclusion: In this world of evidence-based medicine, the BREAST-Q is ideal for a holistic approach in analysing patient satisfaction after BBR. Having local data at hand makes it easier for patients who are interested in undergoing the surgery to associate themselves with other local individuals.peer-reviewe

Adenolipomas : a case series of 16 patients over 5 years

Introduction: An adenolipoma is a benign, rare variant of a lipoma and is histologically very similar to a lipoma but contains eccrine glands amongst the mature adipose tissue. According to our knowledge, this case series of adenolipomas, is the largest one in the literature. The aim is to increase awareness about this variant of lipoma.Method: The data was collected retrospectively from the histopathology department and patients’ notes.Results: We had a total of 16 cases of adenolipomas between 2013 and 2017 in our hospital. 75% of the patients were being managed by General Surgeons. 88% of them occurred in female patients and the patients’ age varied between 15 and 64 years. The most common location of adenolipomas was the thighs and the largest diameter of the histology specimen varied between 15 and 100mm. 31% were encapsulated, 25% had apocrine glands present and 6% had myxoid changes. None of them had mast cells present. No recurrences were documented.Conclusion: It is a benign lesion and awareness amongst pathologists is imperative so that it can be identified histologically.peer-reviewe

Comparative study of COVID and pulmonary fibrotic CT lung images using siamese networks with VGG16

In this research an algorithm is proposed to produce comparative results between Pulmonary Fibrosis of the lungs and COVID computer tomography lung images for the purpose of research to aid in the field of medical science. The Siamese Network which is based on parallel tandem operation to produce comparative results, is altered by changing or altering the implementation function using the VGG16 neural network. The input data set in the method uses a variation of healthy lung CT images along with CT images of cases with pulmonary fibrosis and COVID. The main aim is to produce a comparative study on the textural variation of the CT images under study to further enhance research outputs in the future with accuracy and less time consumption

Comparative study of COVID and pulmonary fibrotic CT lung images using siamese networks with VGG16

In this research an algorithm is proposed to produce comparative results between Pulmonary Fibrosis of the lungs and COVID computer tomography lung images for the purpose of research to aid in the field of medical science. The Siamese Network which is based on parallel tandem operation to produce comparative results, is altered by changing or altering the implementation function using the VGG16 neural network. The input data set in the method uses a variation of healthy lung CT images along with CT images of cases with pulmonary fibrosis and COVID. The main aim is to produce a comparative study on the textural variation of the CT images under study to further enhance research outputs in the future with accuracy and less time consumption

Identification of bronchopulmonary segment containing COVID abrasions using EG-CNN and Segnet

As the current COVID pandemic is a huge concern, more effective methods are required for treatment and analysis of this disease. If COVID analysis is aided by automated detection of the disease, this will reduce time and also speed up treatment. In this research, the particular bronchopulmonary segment containing COVID is detected to narrow and segregate the treatment area. Computer Tomographic Images are passed through EG-CNN which is modelled with Segnet to detect COVID-19 abrasions. The output of the two CNNs are gated to develop the final result with high accuracy

Correlates of Alcohol Consumption, Drug Usage, Sexual Behaviors, and Knowledge About HIV/AIDS Infection Among Traditional College Students

This study evaluated the correlates of alcohol consumption, drug use, sexual behaviors, and knowledge about HIVPIDS infection among traditional college students attending a university in North Carolina. A Health Behaviors, Self-Rated Health and Quality of Life (QOL) questionnaire was administered to 447 university students. The participants in this study were all identified as traditional college students between the ages of 18 and 23, most of whom were first-year African American students. Results from this study determined significant relationships between alcohol consumption, drug use, protective behaviors, and having sexual intercourse among traditional college students. Most importantly, this study documented statistically significant relationships between how often a person consumed alcohol and sexual intercourse [r(441) = .-325, p \u3c .001], the amount of alcohol consumed on each occasion and sexual intercourse [r(444) = .-207, p \u3c .001], using a condom during sexual intercourse and the number of times a person consumed alcohol, [r(433) = .-136, p \u3c .001], and using protection without any alcohol or drug influences, [r(334) = .-742, p \u3c .001]. Findings are discussed in t m s of their implications on future research and prevention programming

Diagnostic of Cystic Fibrosis in Lung Computer Tomographic Images using Image Annotation and Improved PSPNet Modelling

The research deals with the development of an algorithm for detecting pathological formation in cystic fibrosis using the PSPNet model with focal loss. The model allows data sets to be entered in accordance to their similarities based on their pathological diagnostic signs. The simple and effective algorithm structure groups annotated images, processes them in a multiscale CNN, and localizes areas of cystic fibrosis in the lungs with high accuracy