Zobrazeno 1 - 10
of 352
pro vyhledávání: '"Florin, C."'
The precision of contouring target structures and organs-at-risk (OAR) in radiotherapy planning is crucial for ensuring treatment efficacy and patient safety. Recent advancements in deep learning (DL) have significantly improved OAR contouring perfor
Externí odkaz:
http://arxiv.org/abs/2409.18628
Autor:
Gao, Riqiang, Ghesu, Florin C., Arberet, Simon, Basiri, Shahab, Kuusela, Esa, Kraus, Martin, Comaniciu, Dorin, Kamen, Ali
In contemporary radiotherapy planning (RTP), a key module leaf sequencing is predominantly addressed by optimization-based approaches. In this paper, we propose a novel deep reinforcement learning (DRL) model termed as Reinforced Leaf Sequencer (RLS)
Externí odkaz:
http://arxiv.org/abs/2406.01853
Autor:
Islam, Saahil, Murthy, Venkatesh N., Neumann, Dominik, Das, Badhan Kumar, Sharma, Puneet, Maier, Andreas, Comaniciu, Dorin, Ghesu, Florin C.
An accurate detection and tracking of devices such as guiding catheters in live X-ray image acquisitions is an essential prerequisite for endovascular cardiac interventions. This information is leveraged for procedural guidance, e.g., directing stent
Externí odkaz:
http://arxiv.org/abs/2405.01156
Autor:
Amadou, Abdoul Aziz, Singh, Vivek, Ghesu, Florin C., Kim, Young-Ho, Stanciulescu, Laura, Sai, Harshitha P., Sharma, Puneet, Young, Alistair, Rajani, Ronak, Rhode, Kawal
Transesophageal echocardiography (TEE) plays a pivotal role in cardiology for diagnostic and interventional procedures. However, using it effectively requires extensive training due to the intricate nature of image acquisition and interpretation. To
Externí odkaz:
http://arxiv.org/abs/2405.01409
Autor:
Demoustier, Marc, Zhang, Yue, Murthy, Venkatesh Narasimha, Ghesu, Florin C., Comaniciu, Dorin
Device tracking is an important prerequisite for guidance during endovascular procedures. Especially during cardiac interventions, detection and tracking of guiding the catheter tip in 2D fluoroscopic images is important for applications such as mapp
Externí odkaz:
http://arxiv.org/abs/2307.07541
Endovascular guidewire manipulation is essential for minimally-invasive clinical applications (Percutaneous Coronary Intervention (PCI), Mechanical thrombectomy techniques for acute ischemic stroke (AIS), or Transjugular intrahepatic portosystemic sh
Externí odkaz:
http://arxiv.org/abs/2304.09286
This work tackles practical issues which arise when using a tendon-driven robotic manipulator (TDRM) with a long, flexible, passive proximal section in medical applications. Tendon-driven devices are preferred in medicine for their improved outcomes
Externí odkaz:
http://arxiv.org/abs/2301.00337
Autor:
Abdoul Aziz Amadou, Laura Peralta, Paul Dryburgh, Paul Klein, Kaloian Petkov, R. James Housden, Vivek Singh, Rui Liao, Young-Ho Kim, Florin C. Ghesu, Tommaso Mansi, Ronak Rajani, Alistair Young, Kawal Rhode
Publikováno v:
Frontiers in Cardiovascular Medicine, Vol 11 (2024)
IntroductionUltrasound is well-established as an imaging modality for diagnostic and interventional purposes. However, the image quality varies with operator skills as acquiring and interpreting ultrasound images requires extensive training due to th
Externí odkaz:
https://doaj.org/article/13161e4557e341bf8ba15d248740c787
Autor:
Mansoor, Awais, Schmuecking, Ingo, Ghesu, Florin C., Georgescu, Bogdan, Grbic, Sasa, Vishwanath, R.S., Farri, Oladimeji, Ghosh, Rikhiya, Vunikili, Ramya, Zimmermann, Mathis, Sutcliffe, James, Mendelsohn, Steven L., Comaniciu, Dorin, Gefter, Warren B.
Publikováno v:
In Academic Radiology December 2024 31(12):5300-5313
Autor:
Ghesu, Florin C., Georgescu, Bogdan, Mansoor, Awais, Yoo, Youngjin, Neumann, Dominik, Patel, Pragneshkumar, Vishwanath, R. S., Balter, James M., Cao, Yue, Grbic, Sasa, Comaniciu, Dorin
Building accurate and robust artificial intelligence systems for medical image assessment requires not only the research and design of advanced deep learning models but also the creation of large and curated sets of annotated training examples. Const
Externí odkaz:
http://arxiv.org/abs/2201.01283