Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource PHD PhD PhD Thesis Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Relation A related resource 61000311 Title A name given to the resource Respiratory Motion Prediction of Lung Tumor Using Artificial Intelligence Subject The topic of the resource Computer Science Description An account of the resource Managing respiratory motion in radiotherapy for lung cancer presents a formidable and newlinepersistent challenge. The inherent dynamic movement triggered by respiration introduces a notable degree of uncertainty in target delineation, impacting the precision of image-guided radiotherapy. Overlooking the impact of respiratory motion can lead to the emergence of artifacts in images during image acquisition, resulting in inaccuracies in tissue delineation. Moreover, the motion between treatment fractions can induce blurriness in the dose distribution within the treatment process, thereby introducing geometric and dosimetric uncertainties. Additionally, inter-fraction motion can result in the displacement of the distribution of administered doses. Given these complexities, the precise prediction of tumor motion holds the utmost importance in newlineelevating the quality of treatment administration and minimizing radiation exposure to healthy tissues neighboring the pertinent organ during radiotherapy. Nonetheless, achieving the desired level of precision in dose administration remains a formidable task due to the inherent variations in internal patient anatomy across varying time scales and magnitudes. While notable advancements have been witnessed in radiotherapy, attributed to innovations like image guidance tools, which have streamlined treatments, the challenge of accommodating lung tumor motion remains critical, particularly in cases related to newlineradiotherapeutic intervention. Substantial limitations endure despite integrating respiratory-gated techniques in radiation oncology to manage lung tumor motion. Moreover, lung cancer prognosis remains low, irrespective of the recent advancements in radiotherapy. The practice of expanding newlinetreatment margins from the Clinical Treatment Volume (CTV) to encompass the Planning newlineTreatment Volume (PTV) has been adopted as a strategy to amplify treatment outcomes. newlineHowever, this strategy necessitates a trade-off, as it inevitably exposes larger volumes of healthy tissues to radiation. Creator An entity primarily responsible for making the resource Kaushik, Pratim Das Source A related resource from which the described resource is derived Author's Submission Publisher An entity responsible for making the resource available Christ(Deemed to be University) Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Contributor An entity responsible for making contributions to the resource J,Chandra. Rights Information about rights held in and over the resource Open Access Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource English Type The nature or genre of the resource PhD Identifier An unambiguous reference to the resource within a given context <a href="http://hdl.handle.net/10603/560835" target="_blank" rel="noreferrer noopener">http://hdl.handle.net/10603/560835</a>