Adopting transfer learning for neuroimaging: a comparative analysis with a custom 3D convolution neural network model
Por:
Soliman, A, Chang, JR, Etminani, K, Byttner, S, Davidsson, A, Martinez-Sanchis, B, Camacho, V, Bauckneht, M, Stegeran, R, Ressner, M, Agudelo-Cifuentes, M, Chincarini, A, Brendel, M, Rominger, A, Bruffaerts, R, Vandenberghe, R, Kramberger, MG, Trost, M, Nicastro, N, Frisoni, GB, Lemstra, AW, van Berckel, BNM, Pilotto, A, Padovani, A, Morbelli, S, Aarsland, D, Nobili, F, Garibotto, V, Ochoa-Figueroa, M
Publicada:
7 dic 2022
Resumen:
Background: In recent years, neuroimaging with deep learning (DL) algorithms have made remarkable advances in the diagnosis of neurodegenerative disorders. However, applying DL in different medical domains is usually challenged by lack of labeled data. To address this challenge, transfer learning (TL) has been applied to use state-of-the-art convolution neural networks pre-trained on natural images. Yet, there are differences in characteristics between medical and natural images, also image classification and targeted medical diagnosis tasks. The purpose of this study is to investigate the performance of specialized and TL in the classification of neurodegenerative disorders using 3D volumes of 18F-FDG-PET brain scans. Results: Results show that TL models are suboptimal for classification of neurodegenerative disorders, especially when the objective is to separate more than two disorders. Additionally, specialized CNN model provides better interpretations of predicted diagnosis. Conclusions: TL can indeed lead to superior performance on binary classification in timely and data efficient manner, yet for detecting more than a single disorder, TL models do not perform well. Additionally, custom 3D model performs comparably to TL models for binary classification, and interestingly perform better for diagnosis of multiple disorders. The results confirm the superiority of the custom 3D-CNN in providing better explainable model compared to TL adopted ones.
Filiaciones:
Soliman, A:
Halmstad Univ, Ctr Appl Intelligent Syst Res CAISR, Halmstad, Sweden
Chang, JR:
Halmstad Univ, Ctr Appl Intelligent Syst Res CAISR, Halmstad, Sweden
Natl Cheng Kung Univ Tainan, Taipei, Taiwan
Etminani, K:
Halmstad Univ, Ctr Appl Intelligent Syst Res CAISR, Halmstad, Sweden
Byttner, S:
Halmstad Univ, Ctr Appl Intelligent Syst Res CAISR, Halmstad, Sweden
Davidsson, A:
Inst Med & Hlth Sci, Dept Clin Physiol, Linkoping, Sweden
Martinez-Sanchis, B:
La Fe Univ Hosp, Dept Nucl Med, Med Imaging Area, Valencia, Spain
Camacho, V:
Univ Autonoma Barcelona, Serv Med Nucl, Hosp Santa Creu & St Pau, Barcelona, Spain
Bauckneht, M:
IRCCS Osped Policlin San Martino, Nucl Med Unit, Genoa, Italy
Stegeran, R:
Linkoping Univ Hosp, Dept Diagnost Radiol, Linkoping, Sweden
Ressner, M:
Linkoping Univ Hosp, Dept Med Phys, Linkoping, Sweden
Agudelo-Cifuentes, M:
La Fe Univ Hosp, Dept Nucl Med, Med Imaging Area, Valencia, Spain
Chincarini, A:
Natl Inst Nucl Phys INFN, Genoa Sect, Genoa, Italy
Brendel, M:
Ludwig Maximilians Univ Munchen, Univ Hosp, Dept Nucl Med, Munich, Germany
Rominger, A:
Univ Hosp Bern, Dept Nucl Med, Inselspital, Bern, Switzerland
Bruffaerts, R:
Univ Antwerp, Dept Biomed Sci, Antwerp, Belgium
Vandenberghe, R:
KU, Lab Cognit Neurol, Dept Neurosci, Leuven, Belgium
Univ Hosp Leuven, Neurol Dept, Leuven, Belgium
Kramberger, MG:
Univ Med Ctr, Dept Neurol, Ljubljana, Slovenia
Trost, M:
Univ Med Ctr, Dept Neurol, Ljubljana, Slovenia
Univ Ljubljana, Fac Med, Ljubljana, Slovenia
Nicastro, N:
Geneva Univ Hosp, Dept Clin Neurosci, Geneva, Switzerland
Frisoni, GB:
Univ Hosp, Dept Psychiat, LANVIE Lab Neuroimagerie Vieillissement, Geneva, Switzerland
Lemstra, AW:
VU Med Ctr Alzheimer Ctr, Amsterdam, Netherlands
van Berckel, BNM:
Vrije Univ Amsterdam, Dept Radiol & Nucl Med, Amsterdam UMC, Amsterdam Neurosci, Amsterdam, Netherlands
Pilotto, A:
Univ Brescia, Dept Clin & Expt Sci, Neurol Unit, Brescia, Italy
Padovani, A:
IRCCS Osped Policlin San Martino, Nucl Med Unit, Genoa, Italy
Morbelli, S:
Stavanger Univ Hosp, Ctr Age Related Med SESAM, Stavanger, Norway
Aarsland, D:
Univ Genoa, Dept Neurosci DINOGMI, Genoa, Italy
Kings Coll London, Inst Psychiat Psychol & Neurosci, Dept Old Age Psychiat, London, England
Nobili, F:
Univ Genoa, Dept Neurosci DINOGMI, Genoa, Italy
Garibotto, V:
Univ Geneva, Univ Hosp, Div Nucl Med & Mol Imaging, Geneva, Switzerland
Univ Geneva, NIMTLab, Geneva, Switzerland
Ochoa-Figueroa, M:
Inst Med & Hlth Sci, Dept Clin Physiol, Linkoping, Sweden
Linkoping Univ Hosp, Dept Diagnost Radiol, Linkoping, Sweden
Linkoping Univ, Ctr Med Image Sci & Visualizat CMIV, Linkoping, Sweden
Green Published, gold, All Open Access, Gold, Green
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