Asset Details
Do you wish to reserve the book?
Design and Development of Medical Image Processing Experiment System Based on IDL Language
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
Design and Development of Medical Image Processing Experiment System Based on IDL Language
Do you wish to request the book?
Design and Development of Medical Image Processing Experiment System Based on IDL Language
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
Journal Article
Design and Development of Medical Image Processing Experiment System Based on IDL Language
2019
Overview
This paper uses Interactive Data Language (IDL) as a development language to design and implement a lung tumor image processing system with a Client/Server (C/S) structure. During the development process, various business requirements related to the system have been analyzed and the system structure together with detailed business process were designed as a whole. In addition, we also established a database of patients’ lung tumor images to efficiently store and query Computed Tomography (CT) images of lung tumors at various stages of the patient and the images generated during the processing of the system. Finally, the paper elaborated the implementation of the IDL-based lung tumor image processing system, and conducted a performance test and experimental analysis of the system. The system consists of five functional modules: image preprocessing, image segmentation, image reconstruction, image measurement, and image management. This system can automatically calculate quantitative indicators in the delineated area. These features can be used for further tumor differentiation tests, tumor characterization, treatment monitoring, and prognosis assessment. The experimental results show that the system is effective, and also processing speed meets the real-time requirements, and has wide applicability, friendly human-computer interaction, convenient extensibility, good portability, and so on.
Publisher
Bulgarska Akademiya na Naukite / Bulgarian Academy of Sciences,Bulgarian Academy of Sciences
Subject
