Multiple Sclerosis (MS) is a neurodegenerative disease that has gained great attention in recent decades. Recently, techniques such as brain connectivity mapping have shown great potential to be applied to the study of MS, especially in the early stage of the disease. However, there are still challenges in choosing both the therapeutic strategy and the diagnostic imaging, which stimulates the debate between three aspects: 1) the study of the longitudinal progression of MS lesions on the structural and functional networks of the brain and 2) the evaluation the effectiveness of therapeutic strategies widely adopted in the literature (e.g. natalizumab, mitoxantone, beta-interferon-1a and BMT) and 3) the combination of Machine Learning techniques (Machine Learning), mainly associated with Deep Learning, to correlate diagnostic imaging digital therapy along with medication follow-up. Multiple Sclerosis (MS) is a neurodegenerative disease that has gained great attention in recent decades. Recently, techniques such as brain connectivity mapping have shown great potential to be applied to the study of MS, especially in the early stage of the disease. However, there are still challenges in choosing both the therapeutic strategy and the diagnostic imaging, which stimulates the debate between three aspects: 1) the study of the longitudinal progression of MS lesions on the structural and functional networks of the brain and 2) the evaluation the effectiveness of therapeutic strategies widely adopted in the literature (e.g. natalizumab, mitoxantone, beta-interferon-1a and BMT) and 3) the combination of Machine Learning techniques (Machine Learning), mainly associated with Deep Learning, to correlate diagnostic imaging digital therapy along with medication follow-up. Skills: Pesquisa e desenvolvimento (P&D) · Visão computacional · OpenCV

Activities and societies: Development of image processing algorithms to increase the quality of diagnostic imaging tests using diffusion tensor imaging (Diffusion Tensor Imaging).Activities and societies: Development of image processing algorithms to increase the quality of diagnostic imaging tests using diffusion tensor imaging (Diffusion Tensor Imaging). Evaluation of unsupervised machine learning techniques and algorithm adjustments for application in white matter neurodegenerative diseases (Multiple Sclerosis)Evaluation of unsupervised machine learning techniques and algorithm adjustments for application in white matter neurodegenerative diseases (Multiple Sclerosis) Skills: Pesquisa e desenvolvimento (P&D) · Visão computacional · OpenCV

Multiple Sclerosis (MS) is a neurodegenerative disease that has gained great attention in recent decades. Recently, techniques such as brain connectivity mapping have shown great potential to be applied to the study of MS, especially in the early stage of the disease. However, there are still challenges in choosing both the therapeutic strategy and the diagnostic imaging, which stimulates the debate between three aspects: 1) the study of the longitudinal progression of MS lesions on the structural and functional networks of the brain and 2) the evaluation the effectiveness of therapeutic strategies widely adopted in the literature (e.g. natalizumab, mitoxantone, beta-interferon-1a and BMT) and 3) the combination of Machine Learning techniques (Machine Learning), mainly associated with Deep Learning, to correlate diagnostic imaging digital therapy along with medication follow-up.Multiple Sclerosis (MS) is a neurodegenerative disease that has gained great attention in recent decades. Recently, techniques such as brain connectivity mapping have shown great potential to be applied to the study of MS, especially in the early stage of the disease. However, there are still challenges in choosing both the therapeutic strategy and the diagnostic imaging, which stimulates the debate between three aspects: 1) the study of the longitudinal progression of MS lesions on the structural and functional networks of the brain and 2) the evaluation the effectiveness of therapeutic strategies widely adopted in the literature (e.g. natalizumab, mitoxantone, beta-interferon-1a and BMT) and 3) the combination of Machine Learning techniques (Machine Learning), mainly associated with Deep Learning, to correlate diagnostic imaging digital therapy along with medication follow-up. Skills: Pesquisa e desenvolvimento (P&D) · Visão computacional · OpenCV

Activities and societies: Research and Development (R&D)Activities and societies: Research and Development (R&D) Methods for noise reduction in digital images are often used as a preliminary step in many applications. Although anomalous diffusion is a known physical process, it is still not applied to image smoothing like classical diffusion. Here we propose to generalize anisotropic and isotropic diffusion with the concept of anomalous diffusion in image processing, based on image processing, machine learning, deep learning and multidimensional data analysis techniques.Methods for noise reduction in digital images are often used as a preliminary step in many applications. Although anomalous diffusion is a known physical process, it is still not applied to image smoothing like classical diffusion. Here we propose to generalize anisotropic and isotropic diffusion with the concept of anomalous diffusion in image processing, based on image processing, machine learning, deep learning and multidimensional data analysis techniques. Skills: Pesquisa e desenvolvimento (P&D) · Visão computacional · OpenCV

Activities and societies: Curso Comunitário PEIC, Pesquisa no grupo CSIM, criação de softwear para controle de qualidade em Ultrassom de imagem modo B. Activities and societies: Curso Comunitário PEIC, Pesquisa no grupo CSIM, criação de softwear para controle de qualidade em Ultrassom de imagem modo B. Medical Physics undergraduate degree with an emphasis on physics applied to diagnostic and therapeutic medicine based on ionizing and non-ionizing radiation. In addition to the Medical Physics course, I also studied computing applied to digital image processing, focused on pattern recognition techniques, machine learning, deep learning, multidimensional data analysisMedical Physics undergraduate degree with an emphasis on physics applied to diagnostic and therapeutic medicine based on ionizing and non-ionizing radiation. In addition to the Medical Physics course, I also studied computing applied to digital image processing, focused on pattern recognition techniques, machine learning, deep learning, multidimensional data analysis Skills: Pesquisa e desenvolvimento (P&D) · Visão computacional · OpenCV

Líder de equipe oferecendo coordenação, design de soluções e pesquisas com uso de Inteligência Artificial, Machine Learning e Data Science para desafios de saúde personalizada e medicina digital.

I am responsible to achieve continuous improvement in several knowledge and application areas in Nuveo, mostly regarding Machine Learning, Artificial Intelligence, and Software Engineering. Skills: Oratória · Aprendizagem profunda · Modelagem preditiva · Capacidade analítica · TensorFlow · Keras · OpenCV · Pesquisa e desenvolvimento (P&D) · Liderança de equipe · Liderança · Comunicação · Visão computacional

Data scientist dedicated to document/image processing and artificial intelligence (machine learning) applied on Optical Character Recognition (OCR).Data scientist dedicated to document/image processing and artificial intelligence (machine learning) applied on Optical Character Recognition (OCR). Skills: Aprendizagem profunda · Linux · Modelagem preditiva · Capacidade analítica · TensorFlow · Keras · OpenCV · Liderança de equipe · Liderança · Comunicação · Visão computacional

Controle de Qualidade em Ultrassom modo-B - CQUSControle de Qualidade em Ultrassom modo-B - CQUS BR BR 51 2017 000466-8 · Issued Jun 21, 2017