Analysis of Deep Learning Techniques for Brain Tumour Classification from CT & MRI Images

Brain tumour detection in an initialpoint is a critical step to saving human life. Computed Tomography (CT) and Magnetic Resonance Image (MRI) provide very detailed information about brain tumour tissues. So the segmentation of tumour region is possible from pancreatic CT and brain MRI. CT and MRI is a non-invasive technique and it does not produce any harmful radiation to the patient. The patient suspected of tumour undergoes radiological evaluation such that the area, location and grade of the tumour can be predicted from the CT and MRI analysis. This critical information helps the doctors to decide about further treatment like chemotherapy, surgery, or radiation. The diagnosis requires an accurate and very fast segmentation and classification of CT and MRI images. But nowadays radiologists are doing this task manually and it is a tedious and time-consuming procedure. Also, there is a chance of variation in the result from one expert to another. Here comes the significance of automatic segmentation and classification of tumour types with the help of computers.The proposed work aims to develop an efficient system that can detect pancreatic and brain tumour and can classify the pancreatic CT and brain MRI into normal, benign or malignant. This work can be categorized into two approaches. Thus the dataset prepared for this research work contains CT and MRI images.The first approach proposes traditional machine learning technologies to achieve the goal. Image pre-processing, feature extraction, segmentation and classification are the various steps of the traditional machine learning method. A detailed investigation is performed through various feature extraction techniques and classification techniques for pancreatic (CT) and brain MRI. Discrete Wavelet Transform (DWT) feature, Grey Level Co-occurrence Matrix (GLCM) feature, Gabor feature, Tamura features and Edge Orientation Histogram (EOH) features and their combinations are used for the extraction of CT and MRI features. Benign tumours are non-cancerous, but malignant tumours are cancerous. In the first approach, the Support Vector Machine (SVM) is the main classifier used for pancreatic CT and brain MRI classification as normal, benign or malignant.In this technology, a huge amount of data and machines with high computational capabilities like Graphic Processing Unit (GPU) are available. Thus the second approach of this paper is to exploit all these available resources to produce accurate results. In this part, deep learning, the latest fast growing technology introduced in 2015 is used for the classification of brain MRI. A Deep Convolutional Neural Networks (DCNN) model is proposed to perform the classification task efficiently. The CNN results are compared with the results of a simple neural network classifier. This method provides accurate and it shows that deep learning based classification outperforms traditional machine learning techniques which produce an accurate result only. This research work again concentrates on the Transfer Learning (TL) methods to classify pancreatic CT and brain MRI

IN VITRO-IN VIVO EVALUATION OF FAST-DISSOLVING TABLETS CONTAINING SOLID DISPERSION OF OXCARBAZEPINE

Objective: Investigation of in vitro/in vivo behaviour of fast-dissolving tablets containing solid dispersions of oxcarbazepine is the focus of the present research work.Methods: The effect of various hydrophilic polymers on the aqueous solubility of oxcarbazepine was studied. Polyethylene glycol 6000 carrier was selected and solid dispersions were prepared by various methods. A total of nine formulations were compressed into fast-dissolving tablets using avicel PH 102 as a directly compressible filler and ac-di-sol, sodium starch glycolate and crospovidone as super disintegrants and evaluated for pre and post compression parameters and in vitro drug release. In vivo studies of the pure drug, optimized formulation and marketed formulation were carried out on male Wistar rats and pharmacokinetic parameters were calculated using the pk function for Microsoft excel.Results: Mathematical analysis of in vitro data suggested that the first order was the most suitable mathematical model for describing the optimized formulation. The first-order plot was found to be fairly linear for optimized formulation as indicated by its high regression value. Stability studies indicated that the effect of storage was insignificant at 5% level of confidence. The optimized formulation has shown Tmax of 0.5 h, which was highly significant (P<0.05) when compared with pure drug and marketed formulation.Conclusion: Therefore, the solid dispersions prepared by melting method using polyethylene glycol 6000 as hydrophilic carrier can be successfully used for the improvement of dissolution of oxcarbazepine and resulted in faster onset of action as indicated by in vitro and in vivo studies

Obstetric and neonatal outcome in multiple pregnancy in rural India: a prospective study

Background: The objective is to study the obstetric and perinatal outcome in multiple pregnancy.Methods: A prospective study of 100 cases of multiple pregnancy was conducted between October 2013 to July 2016. Incidence of relevant factors, complications, characteristic of multiple pregnancy and sequelae of these complications on obstetric and perinatal outcome were analyzed.Results: Incidence of multiple pregnancy was 2%, anaemia was 22%, preterm labour in 62%, severe preeclampsia in 34%, postpartum haemorrhage in 16%’ PPROM in 14%, abortion in 8%, eclampsia in 2%. Incidence of perinatal mortality rate was 240 per 1000 live births and maternal mortality rates was 2000/ 1 lakh live births which was 10 times more compared to singleton pregnancy.Conclusions: Regular antenatal care, prolonging period of gestation near to term, early admission and care will go a long way in reducing maternal and perinatal mortality

Modelling of E-Governance Framework for Mining Knowledge from Massive Grievance Redressal Data

With the massive proliferation of online applications for the citizens with abundant resources, there is a tremendous hike in usage of e-governance platforms. Right from entrepreneur, players, politicians, students, or anyone who are highly depending on web-based grievance redressal networking sites, which generates loads of massive grievance data that are not only challenging but also highly impossible to understand. The prime reason behind this is grievance data is massive in size and they are highly unstructured. Because of this fact, the proposed system attempts to understand the possibility of performing knowledge discovery process from grievance Data using conventional data mining algorithms. Designed in Java considering massive number of online e-governance framework from civilian’s grievance discussion forums, the proposed system evaluates the effectiveness of performing datamining for Big data

Implementation of Vision and Lidar Sensor Fusion Using Kalman Filter Algorithm

Self-driving car is the next milestone of the automation industry. To achieve the level of autonomy expected in a self-driving car, the vehicle needs to be mounted with an assortment of sensors that can help the vehicle to perceive its three dimensional environment better which leads to better decision-making and control of the vehicle. Each sensor possesses different strengths and weaknesses; they can complement each other better when combined. This is done by a technique called sensor fusion wherein data from various sensors are put together in order to enhance the meaning and accuracy of the overall information. In real time implementations, uncertainty in factors that affect the vehicle's motion can lead to overshoot in parameters. In order to avoid that, an estimation filter is used to predict and update the fused values. This project focuses on sensor fusion of Lidar and Vision sensor (camera) followed by estimation using Kalman filter using values available from an online data set. It can be seen how the use of an estimation filter can significantly improve the accuracy in tracking the path of an obstacle

PROBLEMS AND PROSPECTS OF FIELD WORK TRAINING IN SOCIAL WORK EDUCATION: A REVIEW

Abstract: Social work students generally considered field work training as the most important component in their professional education. In social work curriculum, practice and knowledge (theory) are two integral components in the curriculum, and yet they are often regarded as separate and so some extent antithetical (the theoretical†vs. the practicalâ€). A unique feature of fieldwork training is that training and practice take place in the same place. Hence, students are not learning about†a practice as is the case in classroom instruction but learning in†practice. Field placement is one of the most exciting and exhilarating parts of a formal social work education. It is also one of the most challenging. More than anything else, it requires students to look inside themselves and examine themselves as future social workers. However, most of the time, the students will feel better equipped for their professional career after finishing their practicum. The field work goal is to develop the student's competence in the practice of social work. Field education is an experiential form of teaching and learning that takes place in a service setting. Field work practices offered the most opportunity to understand the requirements of the people in the background of prevailing cultural traditions and values and thereby, offered opportunities to indigenize practice. It also gave opportunities for innovation. Thus, the present paper highlights and reviews on the challenges and prospects of field work training in Social Work education

A prospective observational study of adverse drug reactions to antiretroviral therapy: type and risk factors in a tertiary care teaching hospital

Background: To collect demographic details of patients receiving antiretroviral therapy (ART) and study type of adverse drug reactions (ADRs) and risk factors for ADRs to ART and to assess causality, severity, and preventability assessment of the reported ADRs.Methods: A prospective observational study was conducted for 6 months from January 2012 until June 2012 at ART Center, KR Hospital of Mysore Medical College & Research Institute, Mysore. Data were evaluated for patient demography, risk factors for ADRs, type of ADRs. ADRs were also assessed for their causality, severity, and preventability as per the standard algorithm, using SPSS for windows (version 16.0).Results: Out of 158 patients evaluated, majority were of age group of 21-40 years (66.5%). More number of illiterate patients (55.7%) showed ADRs to ART. Most patients were of CD4 count <250 cells/μl (65.82%). Most common regimen which caused ADRs was zidovudine + lamivudine + nevirapine. Most common type of ADRs was anemia (55.06%) and rash (25.31%). On evaluation of the causality of ADRs, majority were found to be possible (89.24%). The severity assessment showed that most of the patients ADRs were of level 3 (93.05%). The preventability assessment showed that 30.38% patients ADRs were preventable.Conclusion: Identifying risk factors are of crucial importance to optimize the initial choice of ARVs regimen before initiating therapy and to prevent severity and complications caused by ART, thereby improving the quality of care to patients on ART

Analysis of Demography and Clinical Profile of Syncope in Children

INTRODUCTION: Syncope1 – derived from the Greek “Synkoptein”, meaning “to cut” or “to break” - is defined as a sudden loss of consciousness and postural tone, because of transient cerebral hypoperfusion, followed by spontaneous recovery. Transient interruption of cerebral blood flow is followed by loss of consciousness within 8 to 10 seconds. Less than 30 ml blood per 100 grams of brain tissue per minute results in syncope. The critical threshold of cerebral hypoperfusion at which syncope ensues is 50% below baseline mean cerebral flow velocity.(Njemanze, 1992) Although syncope in children is usually benign and self-limiting, physical injury may result from unprotected falls. Older children and adolescents may suffer emotional trauma from embarrassment or fear of having epilepsy, cardiac disease or sudden death. The earliest report of breath holding spells was published in1737 by Nicholas Culpepper, who gave the description: There is a disease…. In children from anger or grief, when the spirits are much stirred and run from the heart to the diaphragms forceably, and hinder or stop the breath…. But when the passion ceaseth, this symptom ceaseth. Breath holding spells were described by Abt as occurring in “neuropathic children of neuropathic parents”. Bridge and colleagues stated that children susceptible to breathholding are usually of active energetic types who react vigorously to situations and that episodes were precipitated by “spoiled child reactions”. Breath holding spells were felt to be a sign of a disturbed parent-child relationship by Kanner (1935). Laxdal2 and his associates (1969)reported that 30%of children with breath holding spells had abnormal behaviour, including temper tantrums, hyperactivity and stubbornness. Syncopal episodes occur in late childhood or adolescents in as many as 17% of patients with breath holding spells (Lombroso and Lerman,1967)3. Parenting a child with breath holding spells has been associated with more maternal stress than parenting a child with a convulsive seizure disorder,and parents of BHS are at risk for developing dysfunctional parenting behaviour. Referral of parents to professionals to help with stress and parenting skills should be considered. AIM OF THE STUDY: To study the epidemiology, etiological factor and Clinical profile of syncope in children.DISCUSSION: Total number of cases analysed in our study was 120 during the period of septemder 2009 to august 2010.Incidence of syncope in our study was 57.12cases/lakh/yr compared to Illario bo et al where it was 86.5/lakhs/yr. Mean age of children in our study was 9.5 years with the minimum of 6 months and maximum of 12 yrs. The percentage of syncope in each age group was compared with other studies. In the present study and in other studies it was clear that syncope was common as the age increases because of increased incidence of vasovagal syncope with increasing age and it was statistically significant.CONCLUSION: 1. Among 120 cases majority were coming under the age group of 6 to 12 years(p = 0.001) 2. The mean age of presentation of syncope was 9.5yrs. 3. Female : male ratio was 1.5:1 (p = 0.105). Females were more commonly affected than males. 4. Educational status of the parents have no correlation with the syncopal episode as 66% of them were literate 5. 55.8% children were from lower socio economic status (p = 0.05) 6. Vasovagal syncope was the most common cause which accounts for 40% of cases (n=48). 7. Vasovagal syncope was more common in the morning time. 8. Breath holding spells were more common in children of age group 6mon to 3yrs (90%) & majority were cyanotic (80%). 9. Family history was present in 25% of patients with BHS. 10. Anaemia of mild grade was associated with majority of cases with B.H.S. (76.5%) with statistical significance (p = 0.001) 11. Nutritional status has no corelation . (p > 0.05) . 12. Blood sugar and electrolytes were normal in all patients with syncope. 13. CT brain and EEG showed no significant abnormalities in patients with syncope