Literature DB >> 10413319

Applications of neural network analyses to in vivo 1H magnetic resonance spectroscopy of epilepsy patients.

I J Bakken1, D Axelson, K A Kvistad, E Brodtkorb, B Müller, J Aasly, I S Gribbestad.   

Abstract

A total of 67 in vivo water-suppressed proton magnetic resonance spectra of the temporal lobes were recorded from 15 patients with long standing temporal lobe epilepsy and 13 healthy volunteers. Conventional data analysis indicated slightly lower N-acetyl aspartate levels in epileptic patients compared with controls. For further analysis of data, a spectral region (4.0-1.5 ppm) was used as input for artificial neural network analysis. Correct classification of spectra was obtained in 66 out of 67 cases, disregarding from which side of the brain the spectra were recorded. The ability of the trained network to recognize spectra recorded both contalaterally and ipsilaterally to the epileptic focus strongly indicates bilateral metabolic changes. Artificial neural networks could also be trained to recognize whether the spectra were recorded from the ipsilateral or contralateral side of the epileptic focus, indicating that neural network analysis of in vivo proton MR spectra can be used as an additional tool for pre-surgical lateralization of seizure foci.

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Year:  1999        PMID: 10413319     DOI: 10.1016/s0920-1211(99)00019-4

Source DB:  PubMed          Journal:  Epilepsy Res        ISSN: 0920-1211            Impact factor:   3.045


  5 in total

1.  Fast quantification of proton magnetic resonance spectroscopic imaging with artificial neural networks.

Authors:  Himanshu Bhat; Balasrinivasa Rao Sajja; Ponnada A Narayana
Journal:  J Magn Reson       Date:  2006-09-01       Impact factor: 2.229

2.  Cerebral metabolite differences in adolescents with low birth weight: assessment with in vivo proton MR spectroscopy.

Authors:  Tone F Bathen; Torill E Sjöbakk; Jon Skranes; Ann-Mari Brubakk; Torstein Vik; Marit Martinussen; Gunnar E Myhr; Ingrid S Gribbestad; David Axelson
Journal:  Pediatr Radiol       Date:  2006-05-16

Review 3.  Automated Identification of Surgical Candidates and Estimation of Postoperative Seizure Freedom in Children - A Focused Review.

Authors:  Debopam Samanta; Jules C Beal; Zachary M Grinspan
Journal:  Semin Pediatr Neurol       Date:  2021-08-19       Impact factor: 3.042

4.  Anatomic segmentation improves prostate cancer detection with artificial neural networks analysis of 1H magnetic resonance spectroscopic imaging.

Authors:  Lukasz Matulewicz; Jacobus F A Jansen; Louisa Bokacheva; Hebert Alberto Vargas; Oguz Akin; Samson W Fine; Amita Shukla-Dave; James A Eastham; Hedvig Hricak; Jason A Koutcher; Kristen L Zakian
Journal:  J Magn Reson Imaging       Date:  2013-11-15       Impact factor: 4.813

Review 5.  Artificial Intelligence shaping the future of neurology practice.

Authors:  P W Vinny; V Y Vishnu; M V Padma Srivastava
Journal:  Med J Armed Forces India       Date:  2021-07-01
  5 in total

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