Research Topic: "Color image analysis for staining intensity quantification - its application to medical research and diagnostic purposes"
Research Area: Medical Image Processing
Author: Keerthana Prasad
Applications: Malaria parasite detection, Breast cancer diagnosis, bone cell growth analysis, nerve fibre analysis, correlation of size of ganglion plexus to appendicitis etc 


Research Topic: “Difference based fractal generation and compression”
Research Area: Computer Graphics and image compression
Author: B Dinesh Rao
Applications: Computer Graphics, fabric printing, medical imaging, compression.


Research Topic: Integrating QFD and Six Sigma into Strategic Information Systems Planning using System Dynamics
Research Area: Technology Management
Author: Narendranath Shanbhag
Applications: This project is applied in the area of Technology management. Various quality tools are integrated into the technology planning process using Systems Dynamics to understand the dynamics of the integration process and help with efficient planning techniques. 


Research topic: "Artificial Neural Network based Dissemination Protocol for VANETs"
Area: Artificial Neural Networks & VANETs
Author: Arockiaraj
Applications: It is proposed to design an Artificial Neural Network based dissemination protocol for VANETs (Vehicular Ad-hoc Networks) which are emerging as a new network environment for intelligent transportation systems. The VANETs considered in this work, are based on short-range wireless communication (e.g., IEEE 802.11) between vehicles. VANETs will be a standard feature in the next generation of vehicles. 


Research topic: "Ultra low-power VLSI circuit design techniques for slow varying signal applications".
Author: Prashanth Kumar Shetty
Area: Low-power is a current need in VLSI design. The increasing prominence of portable systems and the need to limit power consumption (and hence, heat dissipation) in very-high density ULSI chips have led to rapid and innovative developments in low-power design during the recent years. The driving forces behind these developments are portable applications requiring low power dissipation and high throughput, such as notebook computers, portable communication devices, hearing aids, pace makers, wrist watches etc. In most of these cases, the requirements of low power consumption must be met along with equally demanding goals of high chip density and high throughput.

Since most of the biomedical signals are slow, varying in nature, the circuit techniques may be well suited for this type of real time biomedical applications. Specific design techniques, such as aggressive voltage scaling, dynamic power-performance management, and energy-efficient signalling, must be employed to adhere to the stringent energy constraint. The constraint itself is set by the energy source, so energy harvesting holds tremendous promise toward enabling sophisticated systems without straining user lifestyle. Further, once harvested, efficient delivery of the low-energy levels, as well as robust operation at the aggressive low-power modes, requires careful understanding and treatment of the specific design limitations that dominate this realm. We outline the performance and power constraints of biomedical devices, and present circuit techniques to achieve complete systems operating down to power levels of microwatts. In all cases, approaches that leverage advanced technology trends are emphasized.

Applications:

1. A Bionic ear processor for the deaf.
2. An ultra low power portable pulse oximeter for measuring oxygen saturation, an important vital sign.
3. Pace Maker
4. Brain-machine interface (Capturing Neurological Signals)
5. ECG / EEG / EMG Signal acquisition and Analysis
6. Bladder pressure sensor etc.

Research topic: “Fast Medical Image Retrieval Techniques”
Author: Harischandra Hebbar
Applications: The world has witnessed a fast paced technological advancement in last few decades which has revolutionised the entire healthcare and patient management systems. One such field which has undergone a complete change in recent times is the management of patient data and medical records. With the advent of the era of digitisation we are witnessing innumerable possibilities of using the large amount of invaluable patient data for completely different and very useful purposes.

One such possibility arises from the fact that all doctors and medical practitioners tend to refer the past cases and their procedures before taking up a critical decision as to how should a case which is not straightforward to approach should be diagnosed with minimum risks of wrong treatment.. This assures them about the safety of the procedures they will be following and makes them aware of the risks involved in it. Hence we can safely assume that a geographically distributed database containing radiograph images along with the entire data related to the case is an invaluable repository for the doctors and medical practitioners. There has been an explosive growth in the acquisition of medical images for clinical diagnosis, and use in medical research and education. Hospitals have been adopting technology such as Picture Archiving and Communication Systems (PACS) and Hospital Information Systems (HIS) to assist in the digital collection, organisation, and storage of patient data. The goal of these systems is to make patient data more accessible. Retrieval of image information from these systems is done using limited text keywords. These keywords, however, do not capture the richness of the features depicted in the image itself. It would be beneficial if the images could be retrieved by their visual content to help improve medical practice, research and education.

Content Based Image Retrieval (CBIR) is the retrieval of images based on visual features such as colour, texture and shape. Reasons for its development are that in many large image databases, traditional methods of image indexing have proven to be insufficient, laborious and extremely time consuming. Content Based Image Retrieval (CBIR) has been a field of interest for several researchers from decades and after years of work it’s probably the right time now that we can think about applications of it in various fields. There is a need to address the challenge of a specialised internet based Content Based Medical Image Retrieval (CBMIR) system that can help the doctors or medical practitioners across the globe in referring the existing medical records before taking a final decision over the diagnosis.