Automated computer-assisted detection system for cerebral aneurysms in time-of-flight magnetic resonance angiography using fully convolutional network

[1] Vlak MH(2011)Prevalence of unruptured intracranial aneurysms, with emphasis on sex, age, comorbidity, country, and time period: a systematic review and meta-analysis Lancet Neurol 10 626-636

[2] Algra A(2014)Diagnosing intracranial aneurysms with MR angiography: systematic review and meta-analysis Stroke 45 119-126

[3] Brandenburg R(2010)A prospective trial of 3T and 1.5T time-of-flight and contrast-enhanced MR angiography in the follow-up of coiled intracranial aneurysms Am J Neuroradiol 31 912-918

[4] Rinkel GJ(2018)Blood vessel segmentation algorithms—review of methods, datasets and evaluation metrics Comput Methods Programs Biomed 158 71-91

[5] Sailer AM(2018)Deep neural network-based computer-assisted detection of cerebral aneurysms in MR angiography J Magn Reson Imaging 47 948-953

[6] Wagemans BA(2017)Feasibility study of a generalized framework for developing computer-aided detection systems—a new paradigm J Digit Imaging 30 629-639

[7] Nelemans PJ(2018)Deep learning for MR angiography: automated detection of cerebral aneurysms Radiology 290 187-194

[8] de Graaf R(2019)HoTPiG: a novel graph-based 3-D image feature set and its applications to computer-assisted detection of cerebral aneurysms and lung nodules Int J Comput Assist Radiol Surg 14 2095-2107

[9] van Zwam WH(2014)A system to detect cerebral aneurysms in multimodality angiographic data sets Med Phys 41 1904-7986

[10] Kaufmann TJ(2018)A framework for intracranial saccular aneurysm detection and quantification using morphological analysis of cerebral angiograms IEEE Access 6 7970-8

[1] Vlak MH(2011)Prevalence of unruptured intracranial aneurysms, with emphasis on sex, age, comorbidity, country, and time period: a systematic review and meta-analysis Lancet Neurol 10 626-636

[2] Algra A(2014)Diagnosing intracranial aneurysms with MR angiography: systematic review and meta-analysis Stroke 45 119-126

[3] Brandenburg R(2010)A prospective trial of 3T and 1.5T time-of-flight and contrast-enhanced MR angiography in the follow-up of coiled intracranial aneurysms Am J Neuroradiol 31 912-918

[4] Rinkel GJ(2018)Blood vessel segmentation algorithms—review of methods, datasets and evaluation metrics Comput Methods Programs Biomed 158 71-91

[5] Sailer AM(2018)Deep neural network-based computer-assisted detection of cerebral aneurysms in MR angiography J Magn Reson Imaging 47 948-953

[6] Wagemans BA(2017)Feasibility study of a generalized framework for developing computer-aided detection systems—a new paradigm J Digit Imaging 30 629-639

[7] Nelemans PJ(2018)Deep learning for MR angiography: automated detection of cerebral aneurysms Radiology 290 187-194

[8] de Graaf R(2019)HoTPiG: a novel graph-based 3-D image feature set and its applications to computer-assisted detection of cerebral aneurysms and lung nodules Int J Comput Assist Radiol Surg 14 2095-2107

[9] van Zwam WH(2014)A system to detect cerebral aneurysms in multimodality angiographic data sets Med Phys 41 1904-7986

[10] Kaufmann TJ(2018)A framework for intracranial saccular aneurysm detection and quantification using morphological analysis of cerebral angiograms IEEE Access 6 7970-8