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Št. zadetkov: 4
Multi-modal medical image segmentation using deep learning
Gašper Podobnik, Tomaž Vrtovec, Bulat Ibragimov
Doktorska disertacija
Oznake: segmentation;deep learning;radiation therapy;computed tomography;magnetic resonance;head and neck cancer;organs-at-risk;
Cancer remains one of the major socioeconomic challenges of modern times. It is among the three leading causes of death globally, accounting for an estimated 9.7 million deaths annually. Over the years, various treatment modalities have been developed, with surgery, chemotherapy, and RT being the mo ...
Leto: 2025 Vir: Fakulteta za elektrotehniko (UL FE)
HaN-Seg
Gašper Podobnik, Primož Strojan, Primož Peterlin, Bulat Ibragimov, Tomaž Vrtovec
Izvirni znanstveni članek
Oznake: samodejna razgradnja slik;slikovna podatkovna zbirka;računalniška tomografija;magnetna resonanca;radioterapija;rak glave in vratu;auto-segmentation;image dataset;computed tomography;magnetic resonance;radiation therapy;head and neck cancer;
Purpose: For the cancer in the head and neck (HaN), radiotherapy (RT) represents an important treatment modality. Segmentation of organs-at-risk (OARs) is the starting point of RT planning, however, existing approaches are focused on either computed tomography (CT) or magnetic resonance (MR) images, ...
Leto: 2023 Vir: Fakulteta za elektrotehniko (UL FE)
HaN-Seg
Gašper Podobnik, Bulat Ibragimov, Elias Tappeiner, Chanwoong Lee, Jin Sung Kim, Zacharia Mesbah, Romain Modzelewski, Yihao Ma, Fan Yang, Mikołaj Rudecki, Marek Wodziński, Primož Peterlin, Primož Strojan, Tomaž Vrtovec
Izvirni znanstveni članek
Oznake: računski izziv;segmentacija;globoko učenje;kritični organi;računalniška tomografija;magnetna resonanca;radioterapija;rak glave in vratu;computational challenge;segmentation;deep learning;organs-at-risk;computed tomography magnetic resonance;radiotherapy;head and neck cancer;
Background and purpose: To promote the development of auto-segmentation methods for head and neck (HaN) radiation treatment (RT) planning that exploit the information of computed tomography (CT) and magnetic resonance (MR) imaging modalities, we organized HaN-Seg: The Head and Neck Organ-at-Risk CT ...
Leto: 2024 Vir: Fakulteta za elektrotehniko (UL FE)
Reinforcement learning-based anatomical maps for pancreas subregion and duct segmentation
Sepideh Amiri, Tomaž Vrtovec, Tamerlan Mustafaev, Christopher L. Deufel, Henrik S. Thomsen, Martin Hylleholt Sillesen, Erik Gudmann Steuble Brandt, Michael Brun Andersen, Christoph Felix Müller, Bulat Ibragimov
Izvirni znanstveni članek
Oznake: analiza medicinskih slik;razpoznavanje oslonilnih točk;segmentacija slik;trebušna slinavka;globoko učenje;spodbujevano učenje;medical image analysis;landmark detection;image segmentation;pancreas region;deep learning;reinforcement learning;
AbstractBackground: The pancreas is a complex abdominal organ with many anatom-ical variations, and therefore automated pancreas segmentation from medicalimages is a challenging application.Purpose: In this paper, we present a framework for segmenting individualpancreatic subregions and the pancreat ...
Leto: 2024 Vir: Fakulteta za elektrotehniko (UL FE)
Št. zadetkov: 4
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