Feasibility, Sustainability, and Effectiveness of the Implementation of "Facility-Team-Driven" Approach for Improving the Quality of Newborn Care in South India.

Objectives: The primary objective of the study was to assess the feasibility and sustainability of the implementation of the point of care quality improvement (POCQI) methodology for improving the quality of neonatal care at the level 2 special newborn care unit (SNCU). Additional objective was to evaluate the effectiveness of the quality improvement (QI) and preterm baby package training model.

Methods: This study was conducted in a level-II SNCU.

Predictive modeling for corrective maintenance of imaging devices from machine logs.

In the cost sensitive healthcare industry, an unplanned downtime of diagnostic and therapy imaging devices can be a burden on the financials of both the hospitals as well as the original equipment manufacturers (OEMs). In the current era of connectivity, it is easier to get these devices connected to a standard monitoring station. Once the system is connected, OEMs can monitor the health of these devices remotely and take corrective actions by providing preventive maintenance thereby avoiding major unplanned downtime.

An analytics based clinical decision support system for CVD risk assessment and management.

Cardiovascular disease (CVD) is a major cause of disability and premature death throughout the world. Acute coronary events and other cardiovascular events frequently occur suddenly, and are often fatal before medical care can be given. Risk factor modification can reduce clinical events and premature death in people with established cardiovascular disease as well as in those who are at high cardiovascular risk due to one or more risk factors.

A method to detect tortuosity of vessel using non imaging ultrasound approach in carotid structure.

Stroke is a leading cause of functional impairments. The typical screening mechanism is to measure localized Peak Systolic Velocity (PSV) and diagnose impending risk associated with stoke by characterizing the PSV values. However, an accurate measurement of PSV using Doppler ultrasound is affected due to the tortuous nature of carotid artery in elder population group as the angle at which acoustic beam strikes the vessel is over or under estimated resulting in improper measure the blood flow velocity.

A machine learning framework for auto classification of imaging system exams in hospital setting for utilization optimization.

In clinical environment, Interventional X-Ray (IXR) system is used on various anatomies and for various types of the procedures. It is important to classify correctly each exam of IXR system into respective procedures and/or assign to correct anatomy. This classification enhances productivity of the system in terms of better scheduling of the Cath lab, also provides means to perform device usage/revenue forecast of the system by hospital management and focus on targeted treatment planning for a disease/anatomy.

Temporal and spectral analysis of internal carotid artery Doppler signal for normal and abnormal flow detection.

Detection of carotid artery stenosis is presently highly dependent on ultrasound imaging systems. This work presents a method that can detect the normal and abnormal blood flow in the carotid structure independent of Doppler angle by analysing the time and spectral domain representation of Doppler signal. In the proposed approach, time and spectral domain based features are extracted from the Doppler signals of internal carotid arteries.

A method for localized computation of Pulse Wave Velocity in carotid structure.

Pulse Wave Velocity (PWV) promises to be a useful clinical marker for noninvasive diagnosis of atherosclerosis. This work demonstrates the ability to perform localized carotid PWV measurements from the distention waveform derived from the Radio Frequency (RF) ultrasound signal using a carotid phantom setup. The proposed system consists of low cost custom-built ultrasound probe and algorithms for envelope detection, arterial wall identification, echo tracking, distension waveform computation and PWV estimation.

Gaussian mixture model based identification of arterial wall movement for computation of distension waveform.

This work proposes a novel Gaussian Mixture Model (GMM) based approach for accurate tracking of the arterial wall and subsequent computation of the distension waveform using Radio Frequency (RF) ultrasound signal. The approach was evaluated on ultrasound RF data acquired using a prototype ultrasound system from an artery mimicking flow phantom. The effectiveness of the proposed algorithm is demonstrated by comparing with existing wall tracking algorithms.

Analysis of sub-anatomic diffusion tensor imaging indices in white matter regions of Alzheimer with MMSE score.

In this study, an attempt has been made to find the correlation between diffusion tensor imaging (DTI) indices of white matter (WM) regions and mini mental state examination (MMSE) score of Alzheimer patients. Diffusion weighted images are obtained from the ADNI database. These are preprocessed for eddy current correction and removal of non-brain tissue.

Identification of brain white matter regions for diagnosis of Alzheimer using Diffusion Tensor Imaging.

Diffusion Tensor Imaging (DTI) technique is widely used to probe the white matter (WM) tracts, which is affected most by neurological disorders. The fractional anisotropy (FA) metric has been used predominantly to study changes in the WM tracts. Here an attempt is made to delineate specific regions of interest in the WM that may be probable indicators for the diagnosis of Alzheimer disease (AD).