Early Detection of Parkinson’s Disease Dementia Using Dual-Sided Multi-scale Convolutional Neural Networks (DSMS-CNN)

Callum Altham; Huaizhong Zhang; Marcello Trovati; Ella Pereira; Nicola Ray; Simon Keller; Antonella Macerollo; Hulya Wieshmann

doi:10.1007/978-981-16-6775-6_17

Early Detection of Parkinson’s Disease Dementia Using Dual-Sided Multi-scale Convolutional Neural Networks (DSMS-CNN)

Callum Altham^*, Huaizhong Zhang, Marcello Trovati, Ella Pereira, Nicola Ray, Simon Keller, Antonella Macerollo, Hulya Wieshmann

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding (ISBN) › peer-review

Abstract

Detecting the potential for Parkinson’s Disease Dementia (PDD) as early as possible is crucial to ensure that quality of life can be maintained. However, the full origins of this condition are unknown and analysing potential causes such as the influence of the Cholinergic Basal Forebrain (cBF) can be challenging due to variation in brain tissue as well as low scan resolution. Additionally, the structure and function of the cBF can span both brain hemispheres, and therefore prove difficult to analyse using a singular deep learning method. In this paper, we propose a multi-scale, dual-sided approach to analysis of regions with low surface area such as the cBF. Initially, images are parsed using super-resolution to increase resolution and contrast. Then, a dual sided multi-scale convolutional neural network (DSMS-CNN) model is proposed to classify subjects as either normal cognition or PDD based on both hemispheres of the cBF together. Ablation studies and comparison experiments with state-of-the-art CNN models show that DSMS-CNN can achieve promising and superior performance.

Original language	English
Title of host publication	Medical Imaging and Computer-Aided Diagnosis - Proceedings of 2022 International Conference on Medical Imaging and Computer-Aided Diagnosis MICAD 2022
Editors	Ruidan Su, Yudong Zhang, Han Liu, Alejandro F Frangi
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	191-201
Number of pages	11
ISBN (Print)	9789811667749
DOIs	https://doi.org/10.1007/978-981-16-6775-6_17
Publication status	Published - 20 Dec 2023
Event	International Conference on Medical Imaging and Computer-Aided Diagnosis, MICAD 2022 - Leicester, United Kingdom Duration: 20 Nov 2022 → 21 Nov 2022

Publication series

Name	Lecture Notes in Electrical Engineering
Volume	810 LNEE
ISSN (Print)	1876-1100
ISSN (Electronic)	1876-1119

Conference

Conference	International Conference on Medical Imaging and Computer-Aided Diagnosis, MICAD 2022
Country/Territory	United Kingdom
City	Leicester
Period	20/11/22 → 21/11/22

Keywords

Convolutional neural network
Magnetic resonance imaging
Parkinson’s disease
Parkinson’s disease dementia

Access to Document

10.1007/978-981-16-6775-6_17

Cite this

Altham, C., Zhang, H., Trovati, M., Pereira, E., Ray, N., Keller, S., Macerollo, A., & Wieshmann, H. (2023). Early Detection of Parkinson’s Disease Dementia Using Dual-Sided Multi-scale Convolutional Neural Networks (DSMS-CNN). In R. Su, Y. Zhang, H. Liu, & A. F Frangi (Eds.), Medical Imaging and Computer-Aided Diagnosis - Proceedings of 2022 International Conference on Medical Imaging and Computer-Aided Diagnosis MICAD 2022 (pp. 191-201). (Lecture Notes in Electrical Engineering; Vol. 810 LNEE). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-981-16-6775-6_17

Altham, Callum ; Zhang, Huaizhong ; Trovati, Marcello et al. / Early Detection of Parkinson’s Disease Dementia Using Dual-Sided Multi-scale Convolutional Neural Networks (DSMS-CNN). Medical Imaging and Computer-Aided Diagnosis - Proceedings of 2022 International Conference on Medical Imaging and Computer-Aided Diagnosis MICAD 2022. editor / Ruidan Su ; Yudong Zhang ; Han Liu ; Alejandro F Frangi. Springer Science and Business Media Deutschland GmbH, 2023. pp. 191-201 (Lecture Notes in Electrical Engineering).

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abstract = "Detecting the potential for Parkinson{\textquoteright}s Disease Dementia (PDD) as early as possible is crucial to ensure that quality of life can be maintained. However, the full origins of this condition are unknown and analysing potential causes such as the influence of the Cholinergic Basal Forebrain (cBF) can be challenging due to variation in brain tissue as well as low scan resolution. Additionally, the structure and function of the cBF can span both brain hemispheres, and therefore prove difficult to analyse using a singular deep learning method. In this paper, we propose a multi-scale, dual-sided approach to analysis of regions with low surface area such as the cBF. Initially, images are parsed using super-resolution to increase resolution and contrast. Then, a dual sided multi-scale convolutional neural network (DSMS-CNN) model is proposed to classify subjects as either normal cognition or PDD based on both hemispheres of the cBF together. Ablation studies and comparison experiments with state-of-the-art CNN models show that DSMS-CNN can achieve promising and superior performance.",

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Altham, C , Zhang, H , Trovati, M , Pereira, E, Ray, N, Keller, S, Macerollo, A & Wieshmann, H 2023, Early Detection of Parkinson’s Disease Dementia Using Dual-Sided Multi-scale Convolutional Neural Networks (DSMS-CNN). in R Su, Y Zhang, H Liu & A F Frangi (eds), Medical Imaging and Computer-Aided Diagnosis - Proceedings of 2022 International Conference on Medical Imaging and Computer-Aided Diagnosis MICAD 2022. Lecture Notes in Electrical Engineering, vol. 810 LNEE, Springer Science and Business Media Deutschland GmbH, pp. 191-201, International Conference on Medical Imaging and Computer-Aided Diagnosis, MICAD 2022, Leicester, United Kingdom, 20/11/22. https://doi.org/10.1007/978-981-16-6775-6_17

Early Detection of Parkinson’s Disease Dementia Using Dual-Sided Multi-scale Convolutional Neural Networks (DSMS-CNN). / Altham, Callum ; Zhang, Huaizhong ; Trovati, Marcello et al.
Medical Imaging and Computer-Aided Diagnosis - Proceedings of 2022 International Conference on Medical Imaging and Computer-Aided Diagnosis MICAD 2022. ed. / Ruidan Su; Yudong Zhang; Han Liu; Alejandro F Frangi. Springer Science and Business Media Deutschland GmbH, 2023. p. 191-201 (Lecture Notes in Electrical Engineering; Vol. 810 LNEE).

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding (ISBN) › peer-review

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Altham C , Zhang H , Trovati M , Pereira E, Ray N, Keller S et al. Early Detection of Parkinson’s Disease Dementia Using Dual-Sided Multi-scale Convolutional Neural Networks (DSMS-CNN). In Su R, Zhang Y, Liu H, F Frangi A, editors, Medical Imaging and Computer-Aided Diagnosis - Proceedings of 2022 International Conference on Medical Imaging and Computer-Aided Diagnosis MICAD 2022. Springer Science and Business Media Deutschland GmbH. 2023. p. 191-201. (Lecture Notes in Electrical Engineering). doi: 10.1007/978-981-16-6775-6_17