  Citation: Kurmi, A.; Biswas, S.; Sen, S.; Sinitca, A.; Kaplun, D.; Sarkar, R. An Ensemble of CNN Models for Parkinson’s Disease Detection Using DaTscan Images. Diagnostics 2022, 12, 1173. https://doi.org/10.3390/ diagnostics12051173 Academic Editor: Andreas Kjaer Received: 12 March 2022 Accepted: 4 May 2022 Published: 8 May 2022 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affil- iations. Copyright: © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). diagnostics Article An Ensemble of CNN Models for Parkinson’s Disease Detection Using DaTscan Images Ankit Kurmi 1,† , Shreya Biswas 2,† , Shibaprasad Sen 3 , Aleksandr Sinitca 4 , Dmitrii Kaplun 5 and Ram Sarkar 6, * 1 Department of Computer Science and Engineering, Kalyani Government Engineering College, Kalyani 741235, West Bengal, India; ankitkurmi152@gmail.com 2 Department of Electronics and Telecommunication Engineering, Jadavpur University, Kolkata 700032, West Bengal, India; mimigg443@gmail.com 3 Department of Computer Science and Technology, University of Engineering and Management, Kolkata 700160, West Bengal, India; shibubiet@gmail.com 4 Research Centre for Digital Telecommunication Technologies, Saint Petersburg Electrotechnical University ”LETI”, 197022 St. Petersburg, Russia; amsinitca@etu.ru 5 Department of Automation and Control Processes, Saint Petersburg Electrotechnical University ”LETI”, 197022 St. Petersburg, Russia; dikaplun@etu.ru 6 Department of Computer Science and Engineering, Jadavpur University, Kolkata 700032, West Bengal, India * Correspondence: ram.sarkar@jadavpuruniversity.in † These authors contributed equally to this work. Abstract: Parkinson’s Disease (PD) is a progressive central nervous system disorder that is caused due to the neural degeneration mainly in the substantia nigra in the brain. It is responsible for the decline of various motor functions due to the loss of dopamine-producing neurons. Tremors in hands is usually the initial symptom, followed by rigidity, bradykinesia, postural instability, and impaired balance. Proper diagnosis and preventive treatment can help patients improve their quality of life. We have proposed an ensemble of Deep Learning (DL) models to predict Parkinson’s using DaTscan images. Initially, we have used four DL models, namely, VGG16, ResNet50, Inception-V3, and Xception, to classify Parkinson’s disease. In the next stage, we have applied a Fuzzy Fusion logic-based ensemble approach to enhance the overall result of the classification model. The proposed model is assessed on a publicly available database provided by the Parkinson’s Progression Markers Initiative (PPMI). The achieved recognition accuracy, Precision, Sensitivity, Specificity, F1-score from the proposed model are 98.45%, 98.84%, 98.84%, 97.67%, and 98.84%, respectively which are higher than the individual model. We have also developed a Graphical User Interface (GUI)-based software tool for public use that instantly detects all classes using Magnetic Resonance Imaging (MRI) with reasonable accuracy. The proposed method offers better performance compared to other state-of-the- art methods in detecting PD. The developed GUI-based software tool can play a significant role in detecting the disease in real-time. Keywords: Parkinson’s disease; CNN Model; ensemble method; DaTscan images 1. Introduction Parkinson’s disease (PD) has a prevalence rate of 1% in the over-60 age group, and affects about 0–2 per 1000 people. It is the second most common brain disease after Alzheimer’s disease [1]. A central nervous system disorder, especially those affecting the brain, causes the neurons to degenerate. A person suffering from this disease will experience tremors at rest, bradykinesia (slow movement), rigidity, sleep disturbances, asymmetry in posture, depression, and other such symptoms. In the advanced stages of the disease, PD dementia becomes coarse and patients have difficulty sleeping or concentrating. People with PD lose the nerve endings that produce dopamine, the prime chemical which controls most of the involuntary functions of the body. This might help explain some of Diagnostics 2022, 12, 1173. https://doi.org/10.3390/diagnostics12051173 https://www.mdpi.com/journal/diagnostics