Medical imaging workflows with MATLAB

Overview

Medical images come from multiple sources such as MRI, CT, X-ray, ultrasound, and PET/SPECT. Engineers and scientists must visualize and analyze this multi-domain image data to extract clinically meaningful information and conduct other tasks such as training AI models.

MATLAB provides tools and algorithms for end-to-end medical image analysis and AI workflows – I/O, 3D visualization, segmentation, labeling and analysis of medical image data. This webinar shows the complete medical image analysis workflow for AI applications. You will learn how to import visualize, segment and label medical image data and utilize these data in AI model training.

Highlights

Importing image data and metadata from specialized medical file formats, such as DICOM, NIfTI, and NRRD.
Interactively labeling ground truth data for AI workflows.
Segmenting 2D images or 3D volumes into regions such as bones, tumors, or organs using traditional or deep learning techniques.

About the Presenter

Sammit Jain

Sammit is an AI Application Engineer at MathWorks. He works with Engineers and Scientists across India - helping them develop and deploy AI systems using MATLAB. He has a special interest in using Machine Learning/Deep Learning techniques to solve complex problems in medical imaging, computer vision, and Natural Language Processing (NLP). Prior to joining MathWorks, he worked on Bioimage Analysis and Spine segmentation techniques during his time as a research fellow at Institut Pasteur, Paris. He has a Master’s in Mathematics and a Bachelor’s in Electrical and Electronics Engineering from Birla Institute of Technology and Science (BITS) Pilani – Goa

Spandhana Gonuguntla, PhD

Spandhana is a Senior Customer Success Engineer at MathWorks India. She works with faculty and researchers in India to enable effective use of MATLAB and Simulink in their curriculum and research. She specializes in Data analytics, mathematical modelling, Machine Learning and Deep Learning. She has a PhD in Chemical and Biomolecular Engineering from National University of Singapore and B.Tech in Chemical Engineering from National Institute of Technology, Surathkal. Her focus during her PhD was designing novel smart-actuating systems with smart polymers. She has also contributed as an application scientist developing and standardizing assays for Tip Biosystems - a startup company based out of Singapore.

Product Focus

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