Category Archives: A.I.

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Before your dreams begin to fly, it’s time to check if you buckled it right

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Today’s a big day for us. Its confirmed that we’ve made it to the fourth batch of Google’s Launchpad accelerator for start-ups. The latest class of Launchpad has start-ups from across Asia, Africa, Europe, and Latin America, including six from India. These companies will work closely with Google for six months. They get equity-free support, access to […]

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Segmentation of Images using Deep Learning

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In computer vision, image segmentation is the process of dividing an image into parts and extracting the regions of interest. More precisely, image segmentation is the process of assigning a label to every pixel in an image such that pixels having similar characteristics have the same label. Historically, most problems in computer vision involved using […]

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Medical Video Analytics and Deep Learning

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A wise person once said “A picture speaks a thousand words” citing the amount of information that is self-contained in a picture. Along the same lines, it wouldn’t be grossly wrong to say that “A video illustrates a thousand pictures”. Needless to say, the amount of information that can be extracted from a video is […]

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The art of teaching machines to interpret and analyse medical images

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Ever since the wonder invention of microscope by Anton van Leeuwenhoek and the discovery of the X-rays by Wilhelm Röntgen, the field of medical image analysis has developed into a life saving discipline, offering previously unattained opportunities for diagnosis. Medical images have, since then, played an important role in everyday medical practice. It is even […]

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Manthana: Our Indigenous AI Platform

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We at SigTuple, are building 5 different startups. Actually, we build smart screening solutions for the medical industry – to analyse peripheral blood smears, urine, semen, retinal scans and chest x-rays. These are 5 different startups right there if you look at it. We get asked often – “How are you able to work and […]

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Important Aspects in Smart Segmentation of Medical Objects of Interest

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Segmentation of object is an age old problem in computer vision. Also, it is the first step in many object recognition and tracking tasks. Image segmentation is the process of partitioning a digital image into multiple segments such that each segment make sense of the object of interest. Another view of object segmentation is to […]

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Using Unbalanced Datasets for Deep Learning in Medicine

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Deep learning is now considered a panacea to all classification problems; especially those involving images. This is especially true of the medical diagnostic world which generates several petabytes of data each year. With today’s medicine moving to an evidence based diagnosis, this would increase every year. As such, it is a burgeoning challenge for data […]

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The art of building a “continuously learning” diagnostic tool

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Do medical devices change? Yes, of course. Better and better new versions come out. But is the piece of equipment that you purchased two years ago any smarter today than it was then? Can it do more than what it did two years ago? That’s impossible, right? Wrong! Welcome to SigTuple, the maker of continuously […]

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Image Processing – Geometric Illusion and 3-D Estimates

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Examining blood smears or urine samples through automated microscopy has umpteen number of challenges, some of which were addressed in Bharath’s article on Challenges and Opportunities in Automated Microscopy. In this blog, I would like to continue by outlining many more challenges associated with automated microscopy. While examining urine samples or blood smears through a […]

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The exciting new world of machine learning in healthcare

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The field of artificial intelligence in general, and machine learning in particular, has undergone a sea change in the last few years. The way machine learning works can be briefly summarized as follows: A parameter driven classification algorithm is formulated. This is used to derive “decisions” from “input data”. Some popular choices of classification algorithms […]

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