Do you offer Medical Physics residency training for international students. I have a MSc in Medical Physics with National University of Science and Technology in Zimbabwe. My main research interests is on the application of AI in Medical Physics, My MSc thesis was titled Breast and Cervical Cancer Prediction using Supervised Machine Learning Algorithms. If you could offer any help it'll be greatly appreciated
Thanks for sharing such an elaborate coverage of this topic - found to be very useful for us - Best regards yours sincerely Professor AN Abbasi; Radiation Oncologist; The Aga Khan University Karachi Pakistan
If you are asking about commissioning survey, first you need a Geiger counter to find if there are any hotspots. Then use an ionization chamber survey meter to measure the radiation.
Erratum: On slide 7 a graphite calorimeter is pictured, but incorrectly labelled as a graphite cavity chamber. At ARPANSA: · the graphite calorimeter (pictured) is an absorbed dose to water standard for Co-60/MV · the graphite cavity chamber (not pictured) is an air kerma in air standard for Co-60
@@medicalphysicsuwa when you say work do you mean part time TEAP in conjunction with part time Masters? How would one find the time to do a masters and 35h work weeks?
@@stanleynorris7198 Currently, TEAP positions are quite competitive and there is almost no chance to do a masters and TEAP concurrently. By work we mean the type of jobs that students usually undertake.
Hi, can you tell me where did you got the formula for the quality factor Kq = a (TPR-20.10) + b (TPR-20.10) + c and the values a, b, c? Maybe a link or something? Thank you very much!
This formula is provided by the calibration lab for the chamber calibrated for a centre. It is chamber specific, so the a, b, c for our camber would not be the same as your chamber.
Good keep it up I am from Pakistan and undergraduate student of physics and interested in taking admission in Australia in MS medical physics so please guide me through your RU-vid channel I am waiting your video
Great work. Very good presentation. I have a few suggestions: 1. Before trying deep architectures such as GoogLeNet, it may be worth trying some simple CNN models gradually building up based on the training and validation results. (Easy to see where it starts to overfit) 2. Using PCA for feature extraction is a great choice, but to be able to generalize better, you need a large number of samples to get a better estimate of the Eigen-values and Eigen-vectors. 3. Feature-based techniques in combination with machine learning models (SVM, Random Forest, etc.) may also be a possible solution. Good luck and thanks for uploading!
