Internet of Things Solutions in Radiology

Reading Time: 3 minutes |

August 31, 2022


Healthcare / IOT


Internet of Things Solutions in Radiology

The Internet of Things (IoT) in the healthcare sector has improved workflow and patient satisfaction along with better equipment utilization-thanks to the skyrocketing demand for wearable smart devices. In radiology, IoT plays a crucial role by integrating smart devices and mobile phones into the workflow of radiographic diagnostics.

IoT in radiology is proving to be safe and efficient as it connects several pieces of equipment. This allows the sensors to be connected to the internet and manage inventory more efficiently. These technological developments transform imaging informatics into a more personalized and precise system, allowing us to connect with patients in a better way.

Some of the IoT Based Start-ups

Nines is a teleradiology startup that helps radiologists triage medical cases. The software helps in processing radiologic images on a first-come, first-serve basis. It generates a report that also considers patient history from the electronic health record systems.

Aldoc is a startup that offers deep learning algorithms to analyze radiological imaging along with clinical data more effectively. This helps the radiologists complete their cases quicker.

Zebra is assisting radiologists with its revolutionary AI technology to manage their hectic workload.

Deerfield Imaging at IMRIS improves patient outcomes by assisting surgeons at various planning, product integration, and clinical workflows to evaluate the diagnostic quality scans in operating room suites. MR and CT scanners are transported to the patient by the IMRIS Surgical Theatre. This is done by ceiling-mounted rails and other IMRIS imaging technology and is in demand in many hospitals to take care of the patients’ diagnostic and treatment needs related to neurosurgical, spinal, and orthopedics.

MARS Bioimaging develops spectral CT scanners that enable researchers to perform experiments related to human imaging ranging from cancer detection to the development of novel contrast agents.

DDH has created an image analytical platform that automates and simplifies radiological imaging with the help of different deep learning models integrated to facilitate the entire body’s evaluation for structural and functional information.

Similarly, Brainomix has developed a deep learning algorithm for imaging stroke in an improved manner and providing decision-support solutions to hospitals worldwide. QUIBIM is a biotech company dedicated to medical image processing and extraction of imaging biomarkers for medical imaging workflows. Dia is a similar startup that uses pattern recognition and machine learning algorithms for cognitive image processing.

VIDA offers quantitative lung analysis for COPD, emphysema, and asthma, establishing objective, reproducible and quantitative. Therapixel uses specialized artificial intelligence algorithms for medical image analytics as it has a touch-less image navigation system designed for operating theaters: interventional radiology or surgery

Robotics helps practitioners in analyzing medical images leveraging machine learning algorithms. Likewise, offers powerful algorithms to assist pathologists to perform diagnostic tasks on a day-to-day basis.

Kinect is a medical startup with a technology that obtains motion-related functional information from X-ray image series and presents it as a kinetic image. This aids the diagnostician in performing a better diagnosis of moving organs. Moreover, since there are fewer contrast material and X-ray doses needed in this technology, kinetic imaging also makes fluoroscopy and angiography safer.

Future scope

There is an estimated growth of $254.2 billion in 2026 in the global IoT business in the healthcare sector, as per the reports of AllTheResearch. There is maximum demand for smart wearable devices such as smart watches and sensor-enabled smart shirts to monitor patients’ location and well-being. This is heading for even further growth as machine learning, and deep learning techniques can be integrated into these sensor-laden devices to obtain a remote real-time patient data analysis.

IoT in radiology has added momentum to improved digital healthcare and Telemedicine. These devices help remotely monitor the patient data even when they do not physically visit the hospitals’ doctors while they remain at home. There is an ever-increasing demand in healthcare to stay connected to offer continuous monitoring.

Overall, a huge transformation will be seen in healthcare practices that invest in smart technologies and connected machines via IoT in their business. Reports show that manufacturers and pharmaceutical businesses based on IoT-enabled technology positively impacted the investments and equipment manufacturers in 2021. Such technological advances are of utmost importance in the backdrop of the COVID-19 pandemic, where staying healthy and safe is the most significant deciding factor in determining patient convenience in healthcare.

How useful was this post?

Click on a star to rate it!

Average rating 0 / 5. Vote count: 0

No votes so far! Be the first to rate this post.

Related Insights

Food Supply Chain - WhatNext

Food Supply Chain and Internet of Things

Driver Monitoring using AI -WhatNext

Driver Monitoring using Artificial Intelligence

Quantum Computing - WhatNext

Quantum Computing in Car Manufacturing

Sustainable Agriculture - WhatNext

Sustainable Agriculture using Synthetic Biology

Potential of Living Medicines - WhatNext

Potential of Living Medicines