| Educational guide School of Engineering |
english |
| Biomedical Data Science (2022) |
 Subjects |
| MEDICAL IMAGING |
 
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| IDENTIFYING DATA | 2022_23 | |||||||||||||||||
| Subject (*) | MEDICAL IMAGING | Code | 17705104 | |||||||||||||||
| Study programme |
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Cycle | 2nd | |||||||||||||||
| Descriptors | Credits | Type | Year | Period | Exam timetables and dates | |||||||||||||
| 4.5 | Compulsory | First | 1Q |
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| Modality and teaching language | See working groups | |||||||||||||||||
| Prerequisites | ||||||||||||||||||
| Department | Electronic, Electric and Automatic Engineering Computer Engineering and Mathematics |
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| Coordinator |
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simone.balocco@urv.cat oliver.diaz@urv.cat roser.sala@urv.cat jorge.bernal@urv.cat |
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| Lecturers |
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| Web | ||||||||||||||||||
| General description and relevant information |
This module will establish the foundations of the most commonly used medical imaging techniques: x-ray imaging, ultrasound, magnetic resonance imaging, nuclear imaging, endoscopic and pathological images. For each of the techniques, the image formation process will be described. In addition, various basic processing methods and tools that are performed in each of them to improve image quality will be explored. Such knowledge will be key for the application of more advanced image processing techniques that will be seen throughout the master's degree. |
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| (*)The teaching guide is the document in which the URV publishes the information about all its courses. It is a public document and cannot be modified. Only in exceptional cases can it be revised by the competent agent or duly revised so that it is in line with current legislation. | ||||||||||||||||||
