Google DeepMind to Explore Streamlining Radiotherapy Planning
|
By MedImaging International staff writers Posted on 05 Oct 2016 |
|
Image: Google\'s DeepMind has the capacity to build an artificial intelligence computer that mimics the human brain (Photo courtesy of Google DeepMind).
A collaboration between Google DeepMind (London, United Kingdom) and England’s National Health Service (NHS, London) will evaluate the potential for machine learning in making radiotherapy (RT) planning more efficient.
The collaboration will be through a partnership with University College London Hospital (UCLH; United Kingdom), and will involve analysis of many as 700 former head and neck cancer patients, with the hope that artificial intelligence (AI) machine learning could decrease segmentation process time from four hours to just one. According to DeepMind, the project could also lead to the development of a RT segmentation algorithm with potential applications beyond head and neck cancers.
“Developing machine learning which can automatically differentiate between cancerous and healthy tissue on radiotherapy scans will assist clinicians in planning radiotherapy treatment,” said Yen-Ching Chang, MD, clinical lead for radiotherapy at UCLH. “This has the potential to free up clinicians to spend even more time on patient care, education and research, all of which would be to the benefit of our patients and the populations we serve.”
“This real-world application of artificial intelligence technology is exactly why we set up DeepMind. We’re incredibly excited to be working with the radiotherapy team at UCLH to explore how AI can help to reduce the time it takes to plan radiotherapy treatment for head and neck cancer patients,” said Mustafa Suleyman, co-founder and head of applied AI at Google DeepMind. “We hope this work could lead to real benefits for cancer patients across the country and for the clinicians who treat them.”
DeepMind is a AI company founded in September 2010 which created a neural network that can able to access an external memory like a conventional Turing machine, resulting in a computer that mimics the short-term memory of the human brain; it was acquired by Google in 2014. In July 2016, Google DeepMind partnered with Moorfields Eye Hospital (London, United Kingdom) in a project designed to use AI for the early detection and treatment of preventable eye diseases by analyzing retinal scans.
Related Links:
Google DeepMind
National Health Service
University College London Hospital
The collaboration will be through a partnership with University College London Hospital (UCLH; United Kingdom), and will involve analysis of many as 700 former head and neck cancer patients, with the hope that artificial intelligence (AI) machine learning could decrease segmentation process time from four hours to just one. According to DeepMind, the project could also lead to the development of a RT segmentation algorithm with potential applications beyond head and neck cancers.
“Developing machine learning which can automatically differentiate between cancerous and healthy tissue on radiotherapy scans will assist clinicians in planning radiotherapy treatment,” said Yen-Ching Chang, MD, clinical lead for radiotherapy at UCLH. “This has the potential to free up clinicians to spend even more time on patient care, education and research, all of which would be to the benefit of our patients and the populations we serve.”
“This real-world application of artificial intelligence technology is exactly why we set up DeepMind. We’re incredibly excited to be working with the radiotherapy team at UCLH to explore how AI can help to reduce the time it takes to plan radiotherapy treatment for head and neck cancer patients,” said Mustafa Suleyman, co-founder and head of applied AI at Google DeepMind. “We hope this work could lead to real benefits for cancer patients across the country and for the clinicians who treat them.”
DeepMind is a AI company founded in September 2010 which created a neural network that can able to access an external memory like a conventional Turing machine, resulting in a computer that mimics the short-term memory of the human brain; it was acquired by Google in 2014. In July 2016, Google DeepMind partnered with Moorfields Eye Hospital (London, United Kingdom) in a project designed to use AI for the early detection and treatment of preventable eye diseases by analyzing retinal scans.
Related Links:
Google DeepMind
National Health Service
University College London Hospital
Ultrasonic Pocket Doppler
SD1
Portable Color Doppler Ultrasound Scanner
DCU10
X-ray Diagnostic System
FDX Visionary-A
40/80-Slice CT System
uCT 528
Latest Nuclear Medicine News
- Novel PET Imaging Approach Offers Never-Before-Seen View of Neuroinflammation
- Novel Radiotracer Identifies Biomarker for Triple-Negative Breast Cancer
- Innovative PET Imaging Technique to Help Diagnose Neurodegeneration
- New Molecular Imaging Test to Improve Lung Cancer Diagnosis
- Novel PET Technique Visualizes Spinal Cord Injuries to Predict Recovery
- Next-Gen Tau Radiotracers Outperform FDA-Approved Imaging Agents in Detecting Alzheimer’s
- Breakthrough Method Detects Inflammation in Body Using PET Imaging
- Advanced Imaging Reveals Hidden Metastases in High-Risk Prostate Cancer Patients
- Combining Advanced Imaging Technologies Offers Breakthrough in Glioblastoma Treatment
- New Molecular Imaging Agent Accurately Identifies Crucial Cancer Biomarker
- New Scans Light Up Aggressive Tumors for Better Treatment
- AI Stroke Brain Scan Readings Twice as Accurate as Current Method
- AI Analysis of PET/CT Images Predicts Side Effects of Immunotherapy in Lung Cancer
- New Imaging Agent to Drive Step-Change for Brain Cancer Imaging
- Portable PET Scanner to Detect Earliest Stages of Alzheimer’s Disease
- New Immuno-PET Imaging Technique Identifies Glioblastoma Patients Who Would Benefit from Immunotherapy
Channels
Radiography
view channel
World's Largest Class Single Crystal Diamond Radiation Detector Opens New Possibilities for Diagnostic Imaging
Diamonds possess ideal physical properties for radiation detection, such as exceptional thermal and chemical stability along with a quick response time. Made of carbon with an atomic number of six, diamonds... Read more
AI-Powered Imaging Technique Shows Promise in Evaluating Patients for PCI
Percutaneous coronary intervention (PCI), also known as coronary angioplasty, is a minimally invasive procedure where small metal tubes called stents are inserted into partially blocked coronary arteries... Read more
MRI
view channel
AI Tool Tracks Effectiveness of Multiple Sclerosis Treatments Using Brain MRI Scans
Multiple sclerosis (MS) is a condition in which the immune system attacks the brain and spinal cord, leading to impairments in movement, sensation, and cognition. Magnetic Resonance Imaging (MRI) markers... Read more
Ultra-Powerful MRI Scans Enable Life-Changing Surgery in Treatment-Resistant Epileptic Patients
Approximately 360,000 individuals in the UK suffer from focal epilepsy, a condition in which seizures spread from one part of the brain. Around a third of these patients experience persistent seizures... Read more
AI-Powered MRI Technology Improves Parkinson’s Diagnoses
Current research shows that the accuracy of diagnosing Parkinson’s disease typically ranges from 55% to 78% within the first five years of assessment. This is partly due to the similarities shared by Parkinson’s... Read more
Biparametric MRI Combined with AI Enhances Detection of Clinically Significant Prostate Cancer
Artificial intelligence (AI) technologies are transforming the way medical images are analyzed, offering unprecedented capabilities in quantitatively extracting features that go beyond traditional visual... Read moreUltrasound
view channel
Novel Imaging Method Enables Early Diagnosis and Treatment Monitoring of Type 2 Diabetes
Type 2 diabetes is recognized as an autoimmune inflammatory disease, where chronic inflammation leads to alterations in pancreatic islet microvasculature, a key factor in β-cell dysfunction.... Read more
Ultrasound-Based Microscopy Technique to Help Diagnose Small Vessel Diseases
Clinical ultrasound, commonly used in pregnancy scans, provides real-time images of body structures. It is one of the most widely used imaging techniques in medicine, but until recently, it had little... Read more
General/Advanced Imaging
view channel
AI-Powered Imaging System Improves Lung Cancer Diagnosis
Given the need to detect lung cancer at earlier stages, there is an increasing need for a definitive diagnostic pathway for patients with suspicious pulmonary nodules. However, obtaining tissue samples... Read more
AI Model Significantly Enhances Low-Dose CT Capabilities
Lung cancer remains one of the most challenging diseases, making early diagnosis vital for effective treatment. Fortunately, advancements in artificial intelligence (AI) are revolutionizing lung cancer... Read more
Imaging 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
Global AI in Medical Diagnostics Market to Be Driven by Demand for Image Recognition in Radiology
The global artificial intelligence (AI) in medical diagnostics market is expanding with early disease detection being one of its key applications and image recognition becoming a compelling consumer proposition... Read more
Industry News
view channel
GE HealthCare and NVIDIA Collaboration to Reimagine Diagnostic Imaging
GE HealthCare (Chicago, IL, USA) has entered into a collaboration with NVIDIA (Santa Clara, CA, USA), expanding the existing relationship between the two companies to focus on pioneering innovation in... Read more
Patient-Specific 3D-Printed Phantoms Transform CT Imaging
New research has highlighted how anatomically precise, patient-specific 3D-printed phantoms are proving to be scalable, cost-effective, and efficient tools in the development of new CT scan algorithms... Read more
Siemens and Sectra Collaborate on Enhancing Radiology Workflows
Siemens Healthineers (Forchheim, Germany) and Sectra (Linköping, Sweden) have entered into a collaboration aimed at enhancing radiologists' diagnostic capabilities and, in turn, improving patient care... Read more