DOTmed Home MRI Oncology Ultrasound Molecular Imaging X-Ray Cardiology Health IT Business Affairs
News Home Parts & Service Operating Room CT Women's Health Proton Therapy Endoscopy HTMs Mobile Imaging
SEARCH
Posição atual:
>
> This Story


Início de uma sessão ou Registo to rate this News Story
Forward Printable StoryPrint Comment

 

 

MRI Homepage

Hawaii takes aim at kidney disease with 7T preclinical MR system Will track changes in kidneys to determine disease origins

MR research raises the question: Is it time to ditch the necktie? Compressing the jugular vein and carotid artery reduces cerebral blood flow

The importance of breast MR screening for high-risk patients Experts weigh in on MR's emerging role in breast cancer diagnostics

All-optical ultrasound could pave way for combined MR-ultrasound imaging Three orders of magnitude faster than current optical systems

India hospital where man died in MR accident seeks new machine Adding a second scanner in addition to fixing the first raises concerns

MR okay for cardiac device patients – if done right Consulting with electrophysiologists is essential

Guerbet and IBM Watson to develop AI-based liver diagnostics solution Supports liver diagnostics in CT and MR

Canon showcases new 3T MR research system at meeting in France Generates images comparable to those acquired with 7T

Praxair in deal to sell European assets to Taiyo Nippon Sanso Move is dependent on the successful closing of the Praxair-Linde merger

MITA calls for timely exemption process for Section 301 tariffs Calls for exemption of medical imaging technology

A new study indicates that machine-
learning could indicate the degree of
neurological impairment from acute spinal
cord injury in an MR analysis

Machine learning could diagnose SCI neurological impairment, study says

por John R. Fischer , Staff Reporter
Machine learning may soon be a standard component in diagnosing the extent of neurological damage incurred following a spinal cord injury.

That is a possibility explored by researchers from the University of California, San Francisco, in their new study which assessed multiple algorithms in semiautomated MR analysis to classify patients based on their degree of neurological impairment. The results are set to be presented at the ARRS 2018 Annual Meeting.

Story Continues Below Advertisement

THE (LEADER) IN MEDICAL IMAGING TECHNOLOGY SINCE 1982. SALES-SERVICE-REPAIR

Special-Pricing Available on Medical Displays, Patient Monitors, Recorders, Printers, Media, Ultrasound Machines, and Cameras.This includes Top Brands such as SONY, BARCO, NDS, NEC, LG, EDAN, EIZO, ELO, FSN, PANASONIC, MITSUBISHI, OLYMPUS, & WIDE.



"MR, with its exquisite soft tissue contrast, makes it the ideal modality for sensitively detecting pathologic changes in the spinal cord following traumatic injury," Jason Talbott, assistant professor of radiology & biomedical Imaging at UCSF and an author of the study, told HCB News. "Further, because of the variety of available MRI sequences we can probe specific subtypes of pathology, such as susceptibility weighted imaging for hemorrhage detection; diffusion imaging and DTI for white matter integrity; or T2 for highly sensitive detection of edema and contusion injury."

Utilizing axial T2-wieghted MR radiomic features for classification in cases of acute spinal cord injury (SCI), researchers tested several algorithms on the basis of textural variables.

The proof-of-principle study found that the applications of five of these machine-learning methods were capable of identifying potential prognostic texture features and classifying degrees of impairment with variable accuracy.

In addition to SCI, machine-learning has also showed possible value in predicting which patients would benefit most from prostate multiparametric MR and which with OCD would respond best to cognitive behavioral therapy based on functional MR scans.

Still, many researchers caution against the notion that AI will replace radiologists and physicians, indicating that it is still in its infancy and requires a human element, as argued by neuroscience researchers in a recent study, which found that while able to decode mental activity, machine learning does not comprehend the specific information processing components of the brain.

"While AI can be very useful, or even essential, in neuroengineering (e.g., for exploiting all possible dimensions of brain activity to interface with machines, such as robotic devices for brain or spinal-injured patients), its use in neuroscience – that is, to understand the principles of brain functioning – is questionable, and requires solid hypotheses and theories to interpret the results," Anne-Lise Giraud, a professor at the University of Geneva and an author of the neuroscience study, told HCB News at the time of the story's release.

Talbott regardless see a great future in the application of AI for diagnosing and determining the best course treatment for SCI.

"My grand vision of precision medicine applied to SCI is that one day, in real time at the PACS station, we will have tools that can reliably auto-segment the spinal cord tissue from the MR image, automatically extract a number of pre-determined high yield imaging features from a patient's image, and cross-reference that patient's data with a large data repository containing thousands of SCI patient clinical and radiologic data," he said. "The output would be highly accurate prognostic data related to precise motor and sensory outcomes. Such early injury stratification and prognostic data is essential not just for informing the patient and their family, but for identifying patients to include in clinical trials, especially those involving experimental therapeutic interventions."

The use of testing sets and the variables involved in each trained model of the UCSF study were recorded for accuracy.

MRI Homepage


You Must Be Logged In To Post A Comment

Anuncie
Aumente a Sua Perceção da Marca
Leilões + Vendas Privadas
Comece
O mais melhor preço
Comprar Equipamento/Peças
Encontre
O preço o mais baixo
Notícia diária
Leia
A notícia a mais atrasada
Diretório
Browse tudo
DOTmed Usuários
Ética no DOTmed
Veja o nosso
Programa das éticas
O ouro parte o programa do vendedor
Receba PH
Pedidos
Programa do negociante do serviço do ouro
Receba RFP/PS
Pedidos
Fornecedores de Healthcare
Veja tudo
Ferramentas de HCP
Trabalhos/Treinamento
Achado/suficiência
Um trabalho
Parts Hunter +EasyPay
Comece as peças
Citações
Certificado recentemente
Vista recentemente
Usuários certificados
Recentemente Rated
Vista recentemente
Usuários certificados
Central Rental
Equipamento do aluguel
Para menos
Vender Equipamentos/Peças
Comece
A maioria de dinheiro
Preste serviços de manutenção ao Forum dos técnicos
Ajuda do achado
E conselho
Simples RFP
Comece o equipamento
Citações
Mostra de comércio virtual
Serviço do achado
Para o equipamento
O acesso e o uso deste local são sujeitos aos termos e às condições do nosso OBSERVAÇÃO LEGAL & OBSERVAÇÃO DA PRIVACIDADE
Propriedade de e proprietário DOTmeda .com, Inc. Copyright ©2001-2018 DOTmed.com, Inc.
TODOS OS DIREITOS RESERVADOS