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[1]
Advanced software improves cerebellum analysis for disease diagnosis
Universitat Politècnica de València (UPV)Mar 20 2025 A team of researchers from the Universitat Politècnica de València (UPV) and the French National Centre for Scientific Research (CNRS) has developed the world's most advanced software to study the human cerebellum using high-resolution NMR images. Called DeepCeres, this software will help in the research and diagnosis of diseases such as ALS, schizophrenia, autism and Alzheimer's, among others. The work of the Spanish and French researchers has been published in the prestigious journal NeuroImage. Despite its small size compared to the rest of the brain, the cerebellum contains approximately 50% of all brain neurons and plays a fundamental role in cognitive, emotional and motor functions. As Sergio Morell-Ortega, a project researcher at the ITACA Institute of the Universitat Politècnica de València, explains, segmentation of the cerebellum has until now been a great challenge due to the complexity of its anatomy and the difficulty of differentiating its structures by means of conventional magnetic resonance imaging. 'DeepCeres overcomes all these challenges and is, today, the most accurate tool in the world for measuring such an important structure of the central nervous system as the cerebellum', emphasizes Morell. High accuracy The DeepCeres software is capable of measuring 27 structures of the cerebellum. And it stands out above all for improving the precision of segmentation compared to what is achieved with the methods used to date, thanks mainly to the application of different artificial intelligence tools. Using standard resonance images of 1 cubic millimetre, these are converted into ultra-high resolution images of 0.125 mm3 using deep neural networks. This allows researchers and healthcare professionals to obtain detailed information about the anatomy of the cerebellum without the need for ultra-high-resolution data in the initial image. It's like going from a black-and-white image to a colour image. There is nothing similar currently and, moreover, it is accessible to the entire scientific community." Professor JosĂ© Vicente ManjĂłn, main researcher of the project Applications in neuroscience and clinical practice According to the developers of DeepCeres, the precision in the volumetric quantification of the cerebellum will help in the study of neurological pathologies such as cerebellar ataxia, amyotrophic lateral sclerosis or psychiatric illnesses such as schizophrenia and autism. 'Furthermore, different studies published recently have demonstrated the incidence of the structure of the cerebellum in neurodegenerative diseases such as Alzheimer's', adds Sergio Morell. 15,000 cerebellums in five months To facilitate its use, the UPV and French CNRS teams have developed an online platform that is accessible to research and medical staff. Since its launch just five months ago, DeepCeres has processed images of nearly 15,000 cerebellums. To date, it has been used by experts from many countries, with the greatest impact in the United States and China. Researchers from the Research Institute of Industrial Control Systems and Computing and the Applied Mathematics Department at the Universitat Politècnica de València, the Department of Psychobiology at the University of Valencia, the Medical Imaging Department at La Fe University and Polytechnic Hospital and the FISABIO-PrĂncipe Felipe Biomedical Research Centre Joint Biomedical Imaging Unit have also participated in its development. Universitat Politècnica de València (UPV) Journal reference: Morell-Ortega, S., et al. (2025). DeepCERES: A deep learning method for cerebellar lobule segmentation using ultra-high resolution multimodal MRI. NeuroImage. doi.org/10.1016/j.neuroimage.2025.121063.
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DeepCeres: AI-driven software redefines cerebellum research with detailed imaging
A team of researchers from the Universitat Politècnica de València (UPV) and the French National Center for Scientific Research (CNRS) has developed the world's most advanced software to study the human cerebellum using high-resolution NMR images. Called DeepCeres, this software will help in the research and diagnosis of diseases such as ALS, schizophrenia, autism and Alzheimer's, among others. The work of the Spanish and French researchers has been published in the journal NeuroImage. Despite its small size compared to the rest of the brain, the cerebellum contains approximately 50% of all brain neurons and plays a fundamental role in cognitive, emotional and motor functions. As Sergio Morell-Ortega, a project researcher at the ITACA Institute of the Universitat Politècnica de València, explains, segmentation of the cerebellum has until now been a great challenge due to the complexity of its anatomy and the difficulty of differentiating its structures by means of conventional magnetic resonance imaging. "DeepCeres overcomes all these challenges and is, today, the most accurate tool in the world for measuring such an important structure of the central nervous system as the cerebellum," emphasizes Morell. High accuracy The DeepCeres software is capable of measuring 27 structures of the cerebellum. And it stands out above all for improving the precision of segmentation compared to what is achieved with the methods used to date, thanks mainly to the application of different artificial intelligence tools. "Using standard resonance images of 1 cubic millimeter, these are converted into ultra-high resolution images of 0.125 mm using deep neural networks," adds Professor JosĂ© Vicente ManjĂłn, the main researcher of the project. "This allows researchers and health care professionals to obtain detailed information about the anatomy of the cerebellum without the need for ultra-high-resolution data in the initial image. It's like going from a black-and-white image to a color image. There is nothing similar currently and, moreover, it is accessible to the entire scientific community." Applications in neuroscience and clinical practice According to the developers of DeepCeres, the precision in the volumetric quantification of the cerebellum will help in the study of neurological pathologies such as cerebellar ataxia, amyotrophic lateral sclerosis or psychiatric illnesses such as schizophrenia and autism. "Furthermore, different studies published recently have demonstrated the incidence of the structure of the cerebellum in neurodegenerative diseases such as Alzheimer's," adds Sergio Morell. 15,000 cerebellums in five months To facilitate its use, the UPV and French CNRS teams have developed an online platform that is accessible to research and medical staff. Since its launch just five months ago, DeepCeres has processed images of nearly 15,000 cerebellums. To date, it has been used by experts from many countries, with the greatest impact in the United States and China. Researchers from the Research Institute of Industrial Control Systems and Computing and the Applied Mathematics Department at the Universitat Politècnica de València, the Department of Psychobiology at the University of Valencia, the Medical Imaging Department at La Fe University and Polytechnic Hospital and the FISABIO-PrĂncipe Felipe Biomedical Research Center Joint Biomedical Imaging Unit have also participated in its development.
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Researchers from Spain and France have developed DeepCeres, an advanced AI-driven software that enhances cerebellum imaging, potentially aiding in the diagnosis and research of various neurological disorders.
Researchers from the Universitat Politècnica de València (UPV) and the French National Centre for Scientific Research (CNRS) have developed DeepCeres, a groundbreaking software that utilizes artificial intelligence to analyze the human cerebellum with unprecedented accuracy. This innovative tool, described as the world's most advanced for cerebellum study, has been featured in the prestigious journal NeuroImage 12.
The cerebellum, despite its small size, contains approximately 50% of all brain neurons and plays a crucial role in cognitive, emotional, and motor functions. Sergio Morell-Ortega, a project researcher at the ITACA Institute of UPV, explains that cerebellum segmentation has long been challenging due to its complex anatomy and the limitations of conventional magnetic resonance imaging 1.
DeepCeres overcomes these challenges by leveraging various artificial intelligence tools:
Professor José Vicente Manjón, the project's lead researcher, likens this advancement to "going from a black-and-white image to a color image" 1.
The precision offered by DeepCeres in volumetric quantification of the cerebellum is expected to significantly aid in the study and diagnosis of various neurological and psychiatric conditions, including:
To facilitate its use, the UPV and CNRS teams have developed an online platform accessible to research and medical staff. In just five months since its launch, DeepCeres has processed images of nearly 15,000 cerebellums. The tool has gained traction globally, with particularly strong adoption in the United States and China 12.
The development of DeepCeres involved a collaborative effort from various institutions, including:
This collaborative approach underscores the interdisciplinary nature of the project and its potential for wide-ranging impact in the field of neuroscience and medical imaging.
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