Medical imaging has evolved a long way from the early days of CT scanners and MRIs. 3D Visualization is the new trend in the medical imaging world. It uses medical imaging data sets to create 3D models with the help of emerging technologies like AI and Deep Learning. In this article, we’ll shed some light on how 3D visualization is revolutionizing the healthcare industry.

Though it is in its very early stages, 3D visualization of medical imaging has brought about groundbreaking changes. It comprises the process of visualizing 3D images of datasets collected from Computed Tomography (CT), Micro-Computed Tomography (micro-CT or X-ray), Magnetic Resonance Imaging (MRI), and other sources. It allows healthcare professionals to access new angles, higher resolutions, and details that offer an overall understanding of the organ, without any surgery. In the 3D visualization process, statistical clustering methods, computer graphics algorithms, and image processing techniques are applied to medical images, to aid in understanding and visualizing the data in 3-dimensional space. This has been made possible by the high-speed internet, computers, software, and emerging technologies like Artificial Intelligence and Deep Learning. 

How is 3D Visualization Helping Millions?

Medical imaging saves millions of lives by helping doctors detect and diagnose a wide range of diseases, from cancer to heart conditions. MRIs and CT scan also do a great job, but the 2D images generated through them require doctors to make certain assumptions while diagnosing the medical condition. This visualization technology makes it possible for doctors to create a 3D image of MRIs, provides clearer and high-resolution pictures of blood vessels, organ tissues and bones, without performing surgery, which saves a lot of time and money. Also, 3D visualization allows the addition of realistic lighting effects to create photo-realistic images, making it easier to see the complete organ shape and plan critical surgery.

“Modern radiology is completely dependent on 3D visualization.”

Dr. Frank Rybicki, Professor, and Chair of the University of Ottawa’s radiology department and chief of medical imaging at The Ottawa Hospital.

In the last few years, researchers have come up with significant advancements in 3D imaging that has saved many lives. At Massachusetts General Hospital, 3D visualization of medical imaging is being used to examine patients’ anatomy. This process improves the efficiency of radiologists and ultrasonographers and helps in saving patients’ lives as well. Medicine imaging is evolving rapidly with the application of emerging technologies like AI, and Deep Learning, thus, organizations and stakeholders are investing heavily in medical imaging technology research & development. The global 3D medical imaging market is predicted to reach $15. 6 Billion by 2027.

Computation and AI algorithms have also shortened the image acquisition time and make collecting image data more efficient. Artificial Intelligence’s application in the medical imaging market is predicted to grow up to $264.85 billion by 2026.

AI enables doctors to sift through large volumes of scans and return insights that are critical for 3D visualization. Also, AI algorithms help cut down the image processing time and improve the accuracy of the 3D visualization of the images, while Deep Learning tools like PythonTorch and Deep Neural Networks (DNN) make image recognition, including object detection, image classification, segmentation, activity recognition, optical flow, and pose estimation more accurate. Combined together, AI and Deep Learning provide detailed 3D images of the soft tissues located deep within a human body.

3D visualization of medical imaging using Artificial Intelligence and Deep Learning applications acts as a brand-new tool in medical professionals’ toolbox. It is a useful tool for quick representation of organs and for high-quality demonstrations for treatment and diagnostics.

Digital Imaging and Communications in Medicine (DICOM), a standard for communicating and managing medical imaging data, allows storage and transmission of medical images and is used to connect to several medical imaging instruments and devices. It establishes communication between Picture Archiving and Communication Systems (PACS), a medical imaging technology, and devices like scanners, printers, and computer systems.

Kamal Das, VP – Operations and an expert faculty at Jigsaw Academy, has developed a 3D interactive visualization using DICOM for Pulmonary Embolism. Pulmonary Embolism (PE) is caused by an artery blockage in the lungs. This 3D visualization will result in an interactive plot, which will enable one to zoom in and out and rotate the 3D image.

Jigsaw Academy’s Data Science and Analytics courses like the 11-month in-person Postgraduate Diploma In Data Science (PGD-DS) and the 10-month Integrated Program In Business Analytics (IPBA) (a Future Leaders Program) aim to equip learners in Data Science, Statistical Modeling, Visualization, Big Data, Machine Learning, Artificial Intelligence & Neural Networks, and more. If you want to know more about these courses in emerging technologies, check out our website.

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