New Mount Sinai BMEII Center to Focus on AI in Advanced Imaging
By MedImaging International staff writers Posted on 03 Oct 2019 |

Image: The BMEII researchers will join existing Mount Sinai teams to develop biomedical engineering and imaging technologies to improve the detection, diagnosis, treatment, and prevention of human diseases (Photo courtesy of Mount Sinai Health System).
The Mount Sinai Health System (New York, NY, USA) has announced the creation of the Biomedical Engineering and Imaging Institute (BMEII), the first of its kind in New York City, and one of the few in the world. The BMEII will leverage Mount Sinai’s renowned imaging and nanomedicine programs to establish a broad biomedical engineering research and training programs for its graduate and medical students. It will develop novel medical inventions in the fields of imaging, nanomedicine, artificial intelligence (AI), robotics, sensors, medical devices and computer vision technologies such virtual reality (VR), augmented reality (AR) and extended reality (XR).
The BMEII is projected to be fully operational by early 2020 and will recruit at least nine prestigious principal investigators and their teams. These researchers will join existing Mount Sinai teams to develop cutting-edge biomedical engineering and imaging technologies to improve the detection, diagnosis, treatment, and prevention of a wide range of human diseases such as cancer, cardiovascular, and neurological diseases. Mount Sinai’s Translational and Molecular Imaging Institute, which is at the forefront of brain, heart, and cancer imaging research, along with research in nanomedicine for precision imaging and drug delivery, will be fully incorporated into the BMEII. This will enrich the BMEII’s research programs and have a greater impact on biomedical discoveries and patient care.
The BMEII will focus on three research areas - AI in advanced imaging, next generation medical technologies, and VR, AR and XR. In the research area of AI in advanced imaging, BMEII investigators will create new computational tools and algorithms to accelerate and improve the way radiologists generate, interpret, and deploy clinical imaging technologies to improve the speed and accuracy of diagnosis. They will build upon the successes of Mount Sinai researchers who have already developed radiology augmentation technologies that can rapidly triage the severity of neurologic injuries, accurately characterize the type of cancer a patient may have, and identify the early presence of coronary disease before it was thought to be possible. Another goal will be to streamline the workflow of radiologists, giving clinicians the freedom to focus on the most complex cases. These advancements will lead to earlier detection of a wide range of diseases.
In the research area of next generation medical technologies, BMEII researchers will focus on developing new medical devices to improve patient outcomes. For example, wearable technologies based on smart sensors can alert patients with heart disease to blood pressure or cholesterol level changes so they can avoid a potential cardiac event, or they can alert patients with post-traumatic stress disorder that their stress levels are extraordinarily high. The BMEII also aims to advance robotic surgery by developing more portable, flexible, and miniaturized robotic devices that can be used to improve treatments for many conditions in areas such as cardiology, cancer, orthopedics, and interventional radiology.
In the research area of VR, AR and XR, BMEII researchers will focus on the unexplored use of these digital technologies in several areas of medicine. VR, AR, and XR technologies are poised to significantly improve the way future generations of researchers and physicians are educated and trained, and how patient-specific disease processes are understood, pain and anxiety are treated, and personalized mechanisms of engagement are built between doctors and patients. For example, advanced image acquisition, analysis, and AI can be leveraged to build patient-specific disease process models in order to help surgeons better plan for surgery, guide their work during surgery, analyze results, and drive robotic interventions. These models can also be used to communicate the course of care with patients.
“Our imaging and nanomedicine programs are leaders in the development and application of these novel technologies to improve patients’ diagnosis and treatment,” said Zahi Fayad, PhD, Director of the BMEII. “By integrating AI, sensors, robotics, and VR into our programs, the BMEII will take a transformative leap forward in the implementation of next generation medicine and healthcare for our patients and society.”
Related Links:
Mount Sinai Health System
The BMEII is projected to be fully operational by early 2020 and will recruit at least nine prestigious principal investigators and their teams. These researchers will join existing Mount Sinai teams to develop cutting-edge biomedical engineering and imaging technologies to improve the detection, diagnosis, treatment, and prevention of a wide range of human diseases such as cancer, cardiovascular, and neurological diseases. Mount Sinai’s Translational and Molecular Imaging Institute, which is at the forefront of brain, heart, and cancer imaging research, along with research in nanomedicine for precision imaging and drug delivery, will be fully incorporated into the BMEII. This will enrich the BMEII’s research programs and have a greater impact on biomedical discoveries and patient care.
The BMEII will focus on three research areas - AI in advanced imaging, next generation medical technologies, and VR, AR and XR. In the research area of AI in advanced imaging, BMEII investigators will create new computational tools and algorithms to accelerate and improve the way radiologists generate, interpret, and deploy clinical imaging technologies to improve the speed and accuracy of diagnosis. They will build upon the successes of Mount Sinai researchers who have already developed radiology augmentation technologies that can rapidly triage the severity of neurologic injuries, accurately characterize the type of cancer a patient may have, and identify the early presence of coronary disease before it was thought to be possible. Another goal will be to streamline the workflow of radiologists, giving clinicians the freedom to focus on the most complex cases. These advancements will lead to earlier detection of a wide range of diseases.
In the research area of next generation medical technologies, BMEII researchers will focus on developing new medical devices to improve patient outcomes. For example, wearable technologies based on smart sensors can alert patients with heart disease to blood pressure or cholesterol level changes so they can avoid a potential cardiac event, or they can alert patients with post-traumatic stress disorder that their stress levels are extraordinarily high. The BMEII also aims to advance robotic surgery by developing more portable, flexible, and miniaturized robotic devices that can be used to improve treatments for many conditions in areas such as cardiology, cancer, orthopedics, and interventional radiology.
In the research area of VR, AR and XR, BMEII researchers will focus on the unexplored use of these digital technologies in several areas of medicine. VR, AR, and XR technologies are poised to significantly improve the way future generations of researchers and physicians are educated and trained, and how patient-specific disease processes are understood, pain and anxiety are treated, and personalized mechanisms of engagement are built between doctors and patients. For example, advanced image acquisition, analysis, and AI can be leveraged to build patient-specific disease process models in order to help surgeons better plan for surgery, guide their work during surgery, analyze results, and drive robotic interventions. These models can also be used to communicate the course of care with patients.
“Our imaging and nanomedicine programs are leaders in the development and application of these novel technologies to improve patients’ diagnosis and treatment,” said Zahi Fayad, PhD, Director of the BMEII. “By integrating AI, sensors, robotics, and VR into our programs, the BMEII will take a transformative leap forward in the implementation of next generation medicine and healthcare for our patients and society.”
Related Links:
Mount Sinai Health System
Latest Industry News News
- Bayer and Google Partner on New AI Product for Radiologists
- Samsung and Bracco Enter Into New Diagnostic Ultrasound Technology Agreement
- IBA Acquires Radcal to Expand Medical Imaging Quality Assurance Offering
- International Societies Suggest Key Considerations for AI Radiology Tools
- Samsung's X-Ray Devices to Be Powered by Lunit AI Solutions for Advanced Chest Screening
- Canon Medical and Olympus Collaborate on Endoscopic Ultrasound Systems
- GE HealthCare Acquires AI Imaging Analysis Company MIM Software
- First Ever International Criteria Lays Foundation for Improved Diagnostic Imaging of Brain Tumors
- RSNA Unveils 10 Most Cited Radiology Studies of 2023
- RSNA 2023 Technical Exhibits to Offer Innovations in AI, 3D Printing and More
- AI Medical Imaging Products to Increase Five-Fold by 2035, Finds Study
- RSNA 2023 Technical Exhibits to Highlight Latest Medical Imaging Innovations
- AI-Powered Technologies to Aid Interpretation of X-Ray and MRI Images for Improved Disease Diagnosis
- Hologic and Bayer Partner to Improve Mammography Imaging
- Global Fixed and Mobile C-Arms Market Driven by Increasing Surgical Procedures
- Global Contrast Enhanced Ultrasound Market Driven by Demand for Early Detection of Chronic Diseases
Channels
Radiography
view channel
Novel Breast Imaging System Proves As Effective As Mammography
Breast cancer remains the most frequently diagnosed cancer among women. It is projected that one in eight women will be diagnosed with breast cancer during her lifetime, and one in 42 women who turn 50... Read more
AI Assistance Improves Breast-Cancer Screening by Reducing False Positives
Radiologists typically detect one case of cancer for every 200 mammograms reviewed. However, these evaluations often result in false positives, leading to unnecessary patient recalls for additional testing,... Read moreMRI
view channel
PET/MRI Improves Diagnostic Accuracy for Prostate Cancer Patients
The Prostate Imaging Reporting and Data System (PI-RADS) is a five-point scale to assess potential prostate cancer in MR images. PI-RADS category 3 which offers an unclear suggestion of clinically significant... Read more
Next Generation MR-Guided Focused Ultrasound Ushers In Future of Incisionless Neurosurgery
Essential tremor, often called familial, idiopathic, or benign tremor, leads to uncontrollable shaking that significantly affects a person’s life. When traditional medications do not alleviate symptoms,... Read more
Two-Part MRI Scan Detects Prostate Cancer More Quickly without Compromising Diagnostic Quality
Prostate cancer ranks as the most prevalent cancer among men. Over the last decade, the introduction of MRI scans has significantly transformed the diagnosis process, marking the most substantial advancement... Read moreUltrasound
view channel
Deep Learning Advances Super-Resolution Ultrasound Imaging
Ultrasound localization microscopy (ULM) is an advanced imaging technique that offers high-resolution visualization of microvascular structures. It employs microbubbles, FDA-approved contrast agents, injected... Read more
Novel Ultrasound-Launched Targeted Nanoparticle Eliminates Biofilm and Bacterial Infection
Biofilms, formed by bacteria aggregating into dense communities for protection against harsh environmental conditions, are a significant contributor to various infectious diseases. Biofilms frequently... Read moreNuclear Medicine
view channel
New SPECT/CT Technique Could Change Imaging Practices and Increase Patient Access
The development of lead-212 (212Pb)-PSMA–based targeted alpha therapy (TAT) is garnering significant interest in treating patients with metastatic castration-resistant prostate cancer. The imaging of 212Pb,... Read more
New Radiotheranostic System Detects and Treats Ovarian Cancer Noninvasively
Ovarian cancer is the most lethal gynecological cancer, with less than a 30% five-year survival rate for those diagnosed in late stages. Despite surgery and platinum-based chemotherapy being the standard... Read more
AI System Automatically and Reliably Detects Cardiac Amyloidosis Using Scintigraphy Imaging
Cardiac amyloidosis, a condition characterized by the buildup of abnormal protein deposits (amyloids) in the heart muscle, severely affects heart function and can lead to heart failure or death without... Read moreGeneral/Advanced Imaging
view channel
New AI Method Captures Uncertainty in Medical Images
In the field of biomedicine, segmentation is the process of annotating pixels from an important structure in medical images, such as organs or cells. Artificial Intelligence (AI) models are utilized to... Read more.jpg)
CT Coronary Angiography Reduces Need for Invasive Tests to Diagnose Coronary Artery Disease
Coronary artery disease (CAD), one of the leading causes of death worldwide, involves the narrowing of coronary arteries due to atherosclerosis, resulting in insufficient blood flow to the heart muscle.... Read more
Novel Blood Test Could Reduce Need for PET Imaging of Patients with Alzheimer’s
Alzheimer's disease (AD), a condition marked by cognitive decline and the presence of beta-amyloid (Aβ) plaques and neurofibrillary tangles in the brain, poses diagnostic challenges. Amyloid positron emission... Read more.jpg)
CT-Based Deep Learning Algorithm Accurately Differentiates Benign From Malignant Vertebral Fractures
The rise in the aging population is expected to result in a corresponding increase in the prevalence of vertebral fractures which can cause back pain or neurologic compromise, leading to impaired function... Read moreImaging IT
view channel
New Google Cloud Medical Imaging Suite Makes Imaging Healthcare Data More Accessible
Medical imaging is a critical tool used to diagnose patients, and there are billions of medical images scanned globally each year. Imaging data accounts for about 90% of all healthcare data1 and, until... Read more