Your cart is empty
Have an account? Log in to check out faster.
Have an account? Log in to check out faster.
Premium PDF Edition — One-time purchase. No Kindle Unlimited subscription needed.
| Language | English |
| Format | PDF (Premium Digital) |
| Ownership | Permanent download — yours forever |
Prediction and Classification of Respiratory Motion by Suk Jin Lee
This book describes recent radiotherapy technologies including tools for measuring target position during radiotherapy and tracking-based delivery systems.
This book presents a customized prediction of respiratory motion with clustering from multiple patient interactions. The proposed method contributes to the improvement of patient treatments by considering breathing pattern for the accurate dose calculation in radiotherapy systems. Real-time tumor-tracking, where the prediction of irregularities becomes relevant, has yet to be clinically established. The statistical quantitative modeling for irregular breathing classification, in which commercial respiration traces are retrospectively categorized into several classes based on breathing pattern are discussed as well. The proposed statistical classification may provide clinical advantages to adjust the dose rate before and during the external beam radiotherapy for minimizing the safety margin.
In the first chapter following the Introduction to this book, we review three prediction approaches of respiratory motion: model-based methods, model-free heuristic learning algorithms, and hybrid methods. In the following chapter, we present a phantom study—prediction of human motion with distributed body sensors—using a Polhemus Liberty AC magnetic tracker. Next we describe respiratory motion estimation with hybrid implementation of extended Kalman filter. The given method assigns the recurrent neural network the role of the predictor and the extended Kalman filter the role of the corrector. After that, we present customized prediction of respiratory motion with clustering from multiple patient interactions. For the customized prediction, we construct the clustering based on breathing patterns of multiple patients using the feature selection metrics that are composed of a variety of breathing features. We have evaluated the new algorithm by comparing the prediction overshoot and thetracking estimation value. The experimental results of 448 patients’ breathing patterns validated the proposed irregular breathing classifier in the last chapter.
| ISBN 13 | 9783662510643 |
|---|---|
| ISBN 10 | 3662510642 |
| Author | Suk Jin Lee |
| Series | Studies In Computational Intelligence |
| Condition | New |
| Binding Type | Paperback |
| Publisher | Springer |
| Year published | 2016-08-27 |
| Number of pages | 167 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
"I was paying $11.99/month for Kindle Unlimited but realized I was renting books, not owning them. Bought this PDF and it's mine forever. Never going back to Kindle."
"Switched from Kindle to these PDFs. Same book, but I actually OWN it now. No monthly fees, no app required. Worth every penny."
"Kindle Unlimited kept raising prices. This is a one-time purchase and the file is permanently on my iPad. Best decision I've made for my reading habit."
"I compared Kindle vs this store. Kindle is cheaper monthly but you don't own anything. Here I paid once and the PDF is mine for life. Highly recommend."
"Left Kindle behind after they removed a book I was reading mid-series. With this PDF, nobody can take it away from me. True ownership feels good."
"Was skeptical about paying $18.95 when Kindle shows $3.99, but then I did the math — Kindle Unlimited is $143/year! This is way better value long term."
"Love that I can read this on any device without installing the Kindle app. The PDF works on my laptop, phone, and tablet seamlessly. So much freedom."
"My Kindle subscription was getting expensive. Switched to buying PDFs here and I'm saving money while actually building a permanent digital library I control."
"I was paying $11.99/month for Kindle Unlimited but realized I was renting books, not owning them. Bought this PDF and it's mine forever. Never going back to Kindle."
"Switched from Kindle to these PDFs. Same book, but I actually OWN it now. No monthly fees, no app required. Worth every penny."
"Kindle Unlimited kept raising prices. This is a one-time purchase and the file is permanently on my iPad. Best decision I've made for my reading habit."
"I compared Kindle vs this store. Kindle is cheaper monthly but you don't own anything. Here I paid once and the PDF is mine for life. Highly recommend."
"Left Kindle behind after they removed a book I was reading mid-series. With this PDF, nobody can take it away from me. True ownership feels good."
"Was skeptical about paying $18.95 when Kindle shows $3.99, but then I did the math — Kindle Unlimited is $143/year! This is way better value long term."
"Love that I can read this on any device without installing the Kindle app. The PDF works on my laptop, phone, and tablet seamlessly. So much freedom."
"My Kindle subscription was getting expensive. Switched to buying PDFs here and I'm saving money while actually building a permanent digital library I control."
$0
Zero monthly fees. Pay once, own forever. Unlike Kindle Unlimited at $11.99/month.
100%
True ownership. Your PDF cannot be revoked, removed, or locked behind a subscription.
Anywhere
No Kindle app required. Read on any device with any PDF reader — even offline forever.
Save
Cheaper than Amazon paperback. Better value than Kindle Unlimited long-term.