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3D Technologies for Medical Applications
Study Course Description
Course Description Statuss:Approved
Course Description Version:2.00
Study Course Accepted:02.01.2024 12:16:16
| Study Course Information | |||||||||
| Course Code: | FK_077 | LQF level: | Level 7 | ||||||
| Credit Points: | 2.00 | ECTS: | 3.00 | ||||||
| Branch of Science: | Physics | Target Audience: | Medical Technologies; Dentistry; Medicine; Rehabilitation | ||||||
| Study Course Supervisor | |||||||||
| Course Supervisor: | Jevgenijs Proskurins | ||||||||
| Study Course Implementer | |||||||||
| Structural Unit: | Department of Physics | ||||||||
| The Head of Structural Unit: | |||||||||
| Contacts: | Riga, 26a Anninmuizas boulevard, Floor No.1, Rooms 147 a and b, fizika rsu[pnkts]lv, +371 67061539 | ||||||||
| Study Course Planning | |||||||||
| Full-Time - Semester No.1 | |||||||||
| Lectures (count) | 1 | Lecture Length (academic hours) | 2 | Total Contact Hours of Lectures | 2 | ||||
| Classes (count) | 10 | Class Length (academic hours) | 3 | Total Contact Hours of Classes | 30 | ||||
| Total Contact Hours | 32 | ||||||||
| Study course description | |||||||||
| Preliminary Knowledge: | Knowledge of informatics at the level of the High school curriculum. | ||||||||
| Objective: | To train students in spatial modeling, creation, acquisition, and improvement of spatial anatomical models, as well as preparation for 3D printing. To introduce students to various spatial modeling options and software, to allow students to create different complex digital spatial models and print them out. It is expected that the students who have completed the study course will be able to independently develop and prepare spatial models for 3D printing, using data from radiology examinations, and will be able to apply the acquired knowledge in their professional activities. | ||||||||
| Topic Layout (Full-Time) | |||||||||
| No. | Topic | Type of Implementation | Number | Venue | |||||
| 1 | Lectures | 1.00 | computer room | ||||||
| 2 | Classes | 1.00 | computer room | ||||||
| 3 | Classes | 1.00 | computer room | ||||||
| 4 | Classes | 2.00 | computer room | ||||||
| 5 | Classes | 1.00 | computer room | ||||||
| 6 | Classes | 1.00 | computer room | ||||||
| 7 | Classes | 2.00 | computer room | ||||||
| 8 | Classes | 2.00 | computer room | ||||||
| Assessment | |||||||||
| Unaided Work: | |||||||||
| Assessment Criteria: | |||||||||
| Final Examination (Full-Time): | Exam | ||||||||
| Final Examination (Part-Time): | |||||||||
| Learning Outcomes | |||||||||
| Knowledge: | |||||||||
| Skills: | |||||||||
| Competencies: | |||||||||
| Bibliography | |||||||||
| No. | Reference | ||||||||
| Required Reading | |||||||||
| 1 | Introduction to Machine Learning with Python. by Andreas C. Müller, Sarah Guido. Released September 2016. Publisher(s): O'Reilly Media, Inc. | ||||||||
| 2 | 3D Deep Learning with Python. by Xudong Ma, Vishakh Hegde, Lilit Yolyan. Released October 2022. Publisher(s): Packt Publishing | ||||||||
| Additional Reading | |||||||||
| 1 | Richard Szeliski. Computer Vision: Algorithms and Applications. 2nd ed. The University of Washington, Springer, 2022 | ||||||||
| 2 | Geoff Dougherty. Digital Image Processing for Medical Applications. California State University, Channel Islands, April 2009. | ||||||||
