Classification algorithms with multi-modal data fusion could accurately distinguish neuromyelitis optica from multiple sclerosis

• Published in: NeuroImage clinical Vol. 7; no. C; pp. 306 - 314
• Main Authors: Eshaghi, Arman, Riyahi-Alam, Sadjad, Saeedi, Roghayyeh, Roostaei, Tina, Nazeri, Arash, Aghsaei, Aida, Doosti, Rozita, Ganjgahi, Habib, Bodini, Benedetta, Shakourirad, Ali, Pakravan, Manijeh, Ghana'ati, Hossein, Firouznia, Kavous, Zarei, Mojtaba, Azimi, Amir Reza, Sahraian, Mohammad Ali
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier Inc 01.01.2015; Elsevier
• Subjects: Adult; Algorithms; Bioengineering; Computational diagnosis; Diagnosis, Computer-Assisted - methods; Diagnosis, Differential; Differential diagnosis; Female; Humans; Image Interpretation, Computer-Assisted; Imaging; Life Sciences; Magnetic Resonance Imaging - methods; Male; Multi-modal imaging; Multiple sclerosis; Multiple Sclerosis - diagnosis; Neuromyelitis optica; Neuromyelitis Optica - diagnosis; Neurons and Cognition; Radiology; Regular; Computational diagnosis; Multiple sclerosis; Neuromyelitis optica; Differential diagnosis; Multi-modal imaging

Neuromyelitis optica (NMO) exhibits substantial similarities to multiple sclerosis (MS) in clinical manifestations and imaging results and has long been considered a variant of MS. With the advent of a specific biomarker in NMO, known as anti-aquaporin 4, this assumption has changed; however, the di...