Here is your answer I reckon :
Sayan Kahali, Consultant Research Scientist at TCS.
Currently developing Spiking Neural Network models for low power edge applications.
Works with Sounak Dey - our BrainChip evangelist with TCS.
Key interests around Biomedical image analysis, 3D Medical Imaging, Quantitative Brain MR imaging and related applications.
Very good chance that Sayan has been hired on a project basis to work on Spiking Neural models for Skanray with their IP partners ( Brainchip ) technology
View attachment 68208
Hi
@Quiltman,
This may be of interest considering you posed the question previously whether Sayan has been hired by Tata on a project basis to work on Spiking Neural models for
Skanray with their IP partners ( Brainchip ) technology.
As you can see, Skanray is mentioned in this article in terms of Tata Exlsi's aim to enhance their diagnostic imaging solutions with AI.
Interview
Levitating with Digitisation: India’s Diagnostic Imaging Sector
IMT News Desk1 day ago
Medical imaging systems form a crucial diagnostic tool for radiologists. With the advent of digitisation, medical imaging systems have evolved drastically becoming increasingly patient-centered. Technological advancements and innovations have fuelled the growth of the diagnostic imaging industry in India. Integrating AI, Big Data, data analytics tools, and algorithms helps to augment medical imaging systems which in turn enables healthcare professionals to make informed clinical decisions and timely interventions. Tata Elxsi, an advanced design and technology services organisation has pivoted their focus, investments and strategies towards the healthcare industry’s changing needs and requirements. With the help of extensive use of deep learning technologies, big data, data analytics and AI Tata Elxi’s diagnostic imaging wing is transforming the medical imaging and diagnostics space proving to be a key enabler for personalised and precision medicine.
Harshal Kamalakar Sawant, Practice Head of Healthcare Software Services, Tata Elxsi and
Anup SS, Practice Head, Artificial Intelligence, Tata Elxsi talks to
Sonali Patranabish
The gamut of medical imaging systems has increased phenomenally in recent times with medical professionals reliant on radiology to make their clinical decisions. In what ways does Tata Elxsi leverage the use of technology to boost these medical imaging systems?
Tata Elxsi leverages technology to enhance medical imaging systems in several ways. We utilise advanced algorithms and AI to improve image quality, reduce noise, and enable more accurate diagnoses. Our solutions include image processing, reconstruction techniques, and analysis tools that assist radiologists in interpreting images and detecting abnormalities. By automating routine tasks, we are empowering healthcare professionals to focus on providing personalised patient care. Additionally, Tata Elxsi develops cloud-based platforms that facilitate image sharing, storage, and remote access, enabling collaboration between healthcare providers and improving patient care.
AI and GenAI have made inroads into almost every domain in the healthcare sector. In what way does digitisation empower and pivot the digital imaging industry?
AI-powered algorithms can now analyze medical images with greater accuracy and efficiency than human experts, leading to more precise diagnoses. For instance, GenAI creates synthetic medical images for training and testing purposes, reducing the need for real patient data. These advancements enable faster and more accurate image interpretation, improved patient outcomes, and reduced costs.
Additionally, digitisation facilitates remote and instant image sharing and consultation, improving access to care, especially in underserved areas.
In what ways is Tata Elxsi's Artificial Intelligence Center of Excellence (AICoE) used to empower the diagnostic imaging sector? Could you cite a few of your state-of-the-art AI solutions for medical imaging?
The AICoE is making a significant impact on the healthcare industry at large. Specific to imaging technology, AI has helped immensely in image quality enhancement. Our team has developed AI algorithms that can reduce noise and artefacts in medical images, leading to clearer and more interpretable results. This is particularly important in cases where image quality is compromised due to factors such as patient movement or technical limitations, which can impact the overall diagnosis.
Another area of focus is computer-aided detection (CAD). AI-powered CAD systems can help radiologists identify subtle abnormalities in medical images that may be missed by the human eye. This can lead to earlier detection of diseases and more effective treatment. We are also working on image segmentation, which involves automatically dividing medical images into different regions or structures. This can be useful for quantitative analysis and treatment planning. For example, AI algorithms can accurately segment tumours in CT scans, allowing doctors to measure their size and assess their response to treatment.
In addition to these applications, the AICoE is also exploring the use of AI for predictive analytics. By analysing large datasets of medical images and patient information, AI algorithms can identify patterns and trends that may be indicative of disease progression or treatment response. This can help doctors make more informed decisions about patient care.
From an industry perspective, what sort of opportunities can be expected with an improved focus on digitising the medical imaging system?
We believe that the digitisation of medical imaging systems presents a wealth of opportunities for the healthcare industry. This transformation has the potential to revolutionise various aspects of healthcare delivery and management. One of the primary benefits of digitisation is the improvement in efficiency and cost-effectiveness.
By automating and standardizing processes, healthcare providers can streamline their workflows, significantly reduce manual errors, and optimise resource allocation. This leads to smoother operations and better utilisation of available resources.
Secondly, digitisation also paves the way for enhanced patient care through the use of advanced analytics and AI-powered tools. These technologies enable healthcare professionals to make more accurate and timely diagnoses, develop personalised treatment plans, and implement remote monitoring solutions. As a result, patients can receive more tailored and effective care. Furthermore, the shift towards digital medical imaging systems opens up new business models and revenue streams for companies in the healthcare sector. For instance, organizations can offer cloud-based imaging services, develop data analytics solutions, and create telemedicine platforms. These innovative services can provide additional value to healthcare providers and patients alike.
Lastly, digitisation fosters collaboration and innovation within the healthcare community. Digital platforms facilitate the sharing of data and insights among healthcare providers, potentially accelerating research and development efforts. This collaborative approach can lead to breakthroughs in medical knowledge and treatment methodologies.
How do you foresee this market growing and expanding with precision medicine and imaging getting all the attention?
Precision medicine involves tailoring treatments to individual patients based on their genetic makeup and other factors, thus, it requires highly accurate and detailed medical images. This will drive demand for advanced imaging technologies and software solutions. The development of AI and machine learning algorithms will further enhance the capabilities of medical imaging systems. These technologies can help to improve image quality, detect subtle abnormalities, and provide more accurate diagnoses. The growing adoption of digital health solutions will also create new opportunities for medical imaging.
For example, remote monitoring and telemedicine applications will require high-quality images to enable accurate diagnosis and treatment.
Overall, I foresee a bright future for the medical imaging market with the increasing focus on precision medicine and the advancements in technology.
In your recent partnership with Skanray, how will Tata Elxsi value add to Skanray’s diagnostic imaging solutions?
I am excited about our partnership with Skanray. Our collaboration will leverage Tata Elxsi's expertise in software development, AI, and data analytics to enhance Skanray's diagnostic imaging solutions.
We will focus on developing innovative software platforms that improve image quality, enable more accurate diagnoses, and streamline workflows. Our goal is to provide Skanray's customers with cutting-edge technology that can improve patient outcomes and enhance the overall efficiency of healthcare delivery.
By combining Skanray's deep domain knowledge in medical imaging with Tata Elxsi's technological capabilities, we aim to create a powerful partnership that will drive innovation and advance healthcare.
What does the road ahead look like for Tata Elxsi, do you have plans to further broaden your digital imaging solutions?
The road ahead for Tata Elxsi in digital imaging is filled with opportunities for growth and innovation. We plan to continue expanding our portfolio of digital imaging solutions by leveraging emerging technologies such as AI, machine learning, and cloud computing. This will enable us to provide our customers with even more advanced and sophisticated tools.
Additionally, we are committed to strengthening our partnerships with leading medical device manufacturers to develop integrated solutions that address the evolving needs of healthcare providers.
By focusing on these areas, we believe that Tata Elxsi can maintain its position as a leading provider of digital imaging solutions and contribute to improving patient outcomes and healthcare efficiency.
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