Generation of synthetic training data for SEEG electrodes segmentation

[1] Scheffer IE(2017)ILAE classification of the epilepsies: position paper of the ILAE commission for classification and terminology Epilepsia 58 512-521

[2] Berkovic S(2018)Indications and limits of stereoelectroencephalography (SEEG) Neurophysiol Clinique 48 15-24

[3] Capovilla G(2017)SEEG assistant: a 3DSlicer extension to support epilepsy surgery BMC Bioinf 18 124-220

[4] Connolly MB(2018)Comparison of interactive and automatic segmentation of stereoelectroencephalography electrodes on computed tomography post-operative images: preliminary results Healthcare Technol Lett 5 215-2396

[5] French J(2018)Deep learning algorithms for detection of critical findings in head CT scans: a retrospective study Lancet 392 2388-401

[6] Guilhoto L(2016)Is SEEG safe? A systematic review and meta-analysis of stereoelectro-encephalography-related complications Epilepsia 57 386-240

[7] Hirsch E(2012)CT artifacts: causes and reduction techniques Imag Med 4 229-1381

[8] Jain S(2018)Convolutional neural network based metal artifact reduction in X-ray computed tomography IEEE Trans Med Imag 37 1370-238

[9] Mathern GW(2020)Deep sinogram completion with image prior for metal artifact reduction in CT images IEEE Trans Med Imag 40 228-696

[10] Moshé SL(1999)Metal streak artifacts in x-ray computed tomography: a simulation study IEEE Trans Nucl Sci 46 691-undefined

[1] Scheffer IE(2017)ILAE classification of the epilepsies: position paper of the ILAE commission for classification and terminology Epilepsia 58 512-521

[2] Berkovic S(2018)Indications and limits of stereoelectroencephalography (SEEG) Neurophysiol Clinique 48 15-24

[3] Capovilla G(2017)SEEG assistant: a 3DSlicer extension to support epilepsy surgery BMC Bioinf 18 124-220

[4] Connolly MB(2018)Comparison of interactive and automatic segmentation of stereoelectroencephalography electrodes on computed tomography post-operative images: preliminary results Healthcare Technol Lett 5 215-2396

[5] French J(2018)Deep learning algorithms for detection of critical findings in head CT scans: a retrospective study Lancet 392 2388-401

[6] Guilhoto L(2016)Is SEEG safe? A systematic review and meta-analysis of stereoelectro-encephalography-related complications Epilepsia 57 386-240

[7] Hirsch E(2012)CT artifacts: causes and reduction techniques Imag Med 4 229-1381

[8] Jain S(2018)Convolutional neural network based metal artifact reduction in X-ray computed tomography IEEE Trans Med Imag 37 1370-238

[9] Mathern GW(2020)Deep sinogram completion with image prior for metal artifact reduction in CT images IEEE Trans Med Imag 40 228-696

[10] Moshé SL(1999)Metal streak artifacts in x-ray computed tomography: a simulation study IEEE Trans Nucl Sci 46 691-undefined