Improvement of bowel content segmentation in abdominal CT images using the MONAI project
Medical imaging plays a pivotal role in the diagnosis, treatment planning, and monitoring of various diseases. In particular, abdominal computed tomography (CT) imaging provides invaluable insight into gastrointestinal conditions. Despite its importance, segmenting bowel contents from abdominal CT s...
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| Tipo de recurso: | tesis de maestría |
| Fecha de publicación: | 2025 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/449182 |
| Acceso en línea: | https://hdl.handle.net/2117/449182 |
| Access Level: | acceso abierto |
| Palabra clave: | Imaging systems in medicine Neural networks (Computer science) Abdomen--Ultrasonic imaging MONAI nnUNET Imatges mèdiques CT scans AI Reds neuronals Medical image Neural network Imatgeria mèdica Xarxes neuronals (Informàtica) Ecografia abdominal Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial::Aprenentatge automàtic |
| Sumario: | Medical imaging plays a pivotal role in the diagnosis, treatment planning, and monitoring of various diseases. In particular, abdominal computed tomography (CT) imaging provides invaluable insight into gastrointestinal conditions. Despite its importance, segmenting bowel contents from abdominal CT scans remains a challenging task due to the anatomical variability and complexity of the human abdomen. This thesis investigates the application of the MONAI (Medical Open Network for AI) frame- work to enhance bowel content segmentation. Accurate segmentation is critical for clinical interpretation and decision-making, and MONAI offers a robust, research-oriented foundation for deep learning workflows in medical imaging. An additional goal of this project is to provide thorough documentation of the methods and processes involved, ensuring reproducibility and facilitating future developments as the project continues to evolve. |
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