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An investigation into augmentation and preprocessing for optimising X-ray classification in limited datasets: a case study on necrotising enterocolitis Int. J. CARS (IF 3.0) Pub Date : 2024-04-23 Franciszek Nowak, Ka-Wai Yung, Jayaram Sivaraj, Paolo De Coppi, Danail Stoyanov, Stavros Loukogeorgakis, Evangelos B. Mazomenos
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Laryngeal surface reconstructions from monocular endoscopic videos: a structure from motion pipeline for periodic deformations Int. J. CARS (IF 3.0) Pub Date : 2024-04-23 Justin Regef, Likhit Talasila, Julia Wiercigroch, R. Jun Lin, Lueder A. Kahrs
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EndoSRR: a comprehensive multi-stage approach for endoscopic specular reflection removal Int. J. CARS (IF 3.0) Pub Date : 2024-04-20 Wei Li, Fucang Jia, Wenjian Liu
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From quantitative metrics to clinical success: assessing the utility of deep learning for tumor segmentation in breast surgery Int. J. CARS (IF 3.0) Pub Date : 2024-04-20 Chris Yeung, Tamas Ungi, Zoe Hu, Amoon Jamzad, Martin Kaufmann, Ross Walker, Shaila Merchant, Cecil Jay Engel, Doris Jabs, John Rudan, Parvin Mousavi, Gabor Fichtinger
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Stand in surgeon’s shoes: virtual reality cross-training to enhance teamwork in surgery Int. J. CARS (IF 3.0) Pub Date : 2024-04-20 Benjamin D. Killeen, Han Zhang, Liam J. Wang, Zixuan Liu, Constantin Kleinbeck, Michael Rosen, Russell H. Taylor, Greg Osgood, Mathias Unberath
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The development of a novel navigation system for reverse shoulder arthroplasty and its accuracy: a phantom and cadaveric study Int. J. CARS (IF 3.0) Pub Date : 2024-04-18 Qiyang Zhu, Chenkai Li, Xingqi Fan, Haitao Li, Qingxiang Hu, Yaohua He, Xiaojun Chen
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Design and navigation method of a soft robot for single-port transvesical radical prostatectomy Int. J. CARS (IF 3.0) Pub Date : 2024-04-18 Zefeng Liu, Ru Li, Yongfeng Cao, Le Xie
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Intracranial aneurysm detection: an object detection perspective Int. J. CARS (IF 3.0) Pub Date : 2024-04-17 Youssef Assis, Liang Liao, Fabien Pierre, René Anxionnat, Erwan Kerrien
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A zero-shot reinforcement learning strategy for autonomous guidewire navigation Int. J. CARS (IF 3.0) Pub Date : 2024-04-16 Valentina Scarponi, Michel Duprez, Florent Nageotte, Stéphane Cotin
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Performance changes due to differences among annotating radiologists for training data in computerized lesion detection Int. J. CARS (IF 3.0) Pub Date : 2024-04-16 Yukihiro Nomura, Shouhei Hanaoka, Naoto Hayashi, Takeharu Yoshikawa, Saori Koshino, Chiaki Sato, Momoko Tatsuta, Yuya Tanaka, Shintaro Kano, Moto Nakaya, Shohei Inui, Masashi Kusakabe, Takahiro Nakao, Soichiro Miki, Takeyuki Watadani, Ryusuke Nakaoka, Akinobu Shimizu, Osamu Abe
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Flow diverters treatment planning of small- and medium-sized intracranial saccular aneurysms on the internal carotid artery via constraint-based virtual deployment Int. J. CARS (IF 3.0) Pub Date : 2024-04-15 Zehua Liu, Meng Zhang, Chao Wang, Zhongxiao Wang, Xiangyun Liao, Chubin Ou, Weixin Si
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The development and testing of a smart sensorized guide wire for catheterization in a “blood” vessel phantom to support aortic valve implementation Int. J. CARS (IF 3.0) Pub Date : 2024-04-15 M. Berger, N. Kuhn, M. Pillei, N. Bonaros, T. Senfter
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Take a shot! Natural language control of intelligent robotic X-ray systems in surgery Int. J. CARS (IF 3.0) Pub Date : 2024-04-15 Benjamin D. Killeen, Shreayan Chaudhary, Greg Osgood, Mathias Unberath
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DBH-YOLO: a surgical instrument detection method based on feature separation in laparoscopic surgery Int. J. CARS (IF 3.0) Pub Date : 2024-04-13 Xiaoying Pan, Manrong Bi, Hao Wang, Chenyang Ma, Xianli He
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Can surgical computer vision benefit from large-scale visual foundation models? Int. J. CARS (IF 3.0) Pub Date : 2024-04-12 Navid Rabbani, Adrien Bartoli
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Create virtual dentoskeletal model by superimposing digital dental cast into cone-beam computed tomography scan Int. J. CARS (IF 3.0) Pub Date : 2024-04-10 Reem Shakir Mahmood, Sadiq Jafer Abbas Hamandi, Akmam Hamdy Al-Mahdi
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ImSpect: Image-driven self-supervised learning for surgical margin evaluation with mass spectrometry Int. J. CARS (IF 3.0) Pub Date : 2024-04-10 Laura Connolly, Fahimeh Fooladgar, Amoon Jamzad, Martin Kaufmann, Ayesha Syeda, Kevin Ren, Purang Abolmaesumi, John F. Rudan, Doug McKay, Gabor Fichtinger, Parvin Mousavi
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LensePro: label noise-tolerant prototype-based network for improving cancer detection in prostate ultrasound with limited annotations Int. J. CARS (IF 3.0) Pub Date : 2024-04-10 Minh Nguyen Nhat To, Fahimeh Fooladgar, Paul Wilson, Mohamed Harmanani, Mahdi Gilany, Samira Sojoudi, Amoon Jamzad, Silvia Chang, Peter Black, Parvin Mousavi, Purang Abolmaesumi
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Enhancing robotic telesurgery with sensorless haptic feedback Int. J. CARS (IF 3.0) Pub Date : 2024-04-10 Nural Yilmaz, Brendan Burkhart, Anton Deguet, Peter Kazanzides, Ugur Tumerdem
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FF-ViT: probe orientation regression for robot-assisted endomicroscopy tissue scanning Int. J. CARS (IF 3.0) Pub Date : 2024-04-10 Chi Xu, Alfie Roddan, Haozheng Xu, Giannarou Stamatia
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Cognitive effort detection for tele-robotic surgery via personalized pupil response modeling Int. J. CARS (IF 3.0) Pub Date : 2024-04-08 Regine Büter, Roger D. Soberanis-Mukul, Rohit Shankar, Paola Ruiz Puentes, Ahmed Ghazi, Jie Ying Wu, Mathias Unberath
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On-the-fly point annotation for fast medical video labeling Int. J. CARS (IF 3.0) Pub Date : 2024-04-04 Adrien Meyer, Jean-Paul Mazellier, Jérémy Dana, Nicolas Padoy
Purpose: In medical research, deep learning models rely on high-quality annotated data, a process often laborious and time-consuming. This is particularly true for detection tasks where bounding box annotations are required. The need to adjust two corners makes the process inherently frame-by-frame. Given the scarcity of experts’ time, efficient annotation methods suitable for clinicians are needed
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Robot-assisted biopsy sampling for online Raman spectroscopy cancer confirmation in the operating room Int. J. CARS (IF 3.0) Pub Date : 2024-04-04 David Grajales, William T. Le, Trang Tran, Sandryne David, Frédérick Dallaire, Katherine Ember, Frédéric Leblond, Cynthia Ménard, Samuel Kadoury
Purpose Cancer confirmation in the operating room (OR) is crucial to improve local control in cancer therapies. Histopathological analysis remains the gold standard, but there is a lack of real-time in situ cancer confirmation to support margin confirmation or remnant tissue. Raman spectroscopy (RS), as a label-free optical technique, has proven its power in cancer detection and, when integrated into
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Deep-learning based 3D reconstruction of lower limb bones from biplanar radiographs for preoperative osteotomy planning Int. J. CARS (IF 3.0) Pub Date : 2024-04-04 Tabitha Arn Roth, Moritz Jokeit, Reto Sutter, Lazaros Vlachopoulos, Sandro F. Fucentese, Fabio Carrillo, Jess G. Snedeker, Hooman Esfandiari, Philipp Fürnstahl
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EndoViT: pretraining vision transformers on a large collection of endoscopic images Int. J. CARS (IF 3.0) Pub Date : 2024-04-03 Dominik Batić, Felix Holm, Ege Özsoy, Tobias Czempiel, Nassir Navab
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Incremental regression of localization context for automatic segmentation of ossified ligamentum flavum from CT data Int. J. CARS (IF 3.0) Pub Date : 2024-04-03 Rong Tao, Xiaoyang Zou, Xiaoru Gao, Xinhua Li, Zhiyu Wang, Xin Zhao, Guoyan Zheng, Donghua Hang
Purpose Segmentation of ossified ligamentum flavum (OLF) plays a crucial role in developing computer-assisted, image-guided systems for decompressive thoracic laminectomy. Manual segmentation is time-consuming, tedious, and label-intensive. It also suffers from inter- and intra-observer variability. Automatic segmentation is highly desired. Methods A two-stage, localization context-aware framework
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Multimodal semi-supervised learning for online recognition of multi-granularity surgical workflows Int. J. CARS (IF 3.0) Pub Date : 2024-04-01 Yutaro Yamada, Jacinto Colan, Ana Davila, Yasuhisa Hasegawa
Purpose Surgical workflow recognition is a challenging task that requires understanding multiple aspects of surgery, such as gestures, phases, and steps. However, most existing methods focus on single-task or single-modal models and rely on costly annotations for training. To address these limitations, we propose a novel semi-supervised learning approach that leverages multimodal data and self-supervision
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XRelevanceCAM: towards explainable tissue characterization with improved localisation of pathological structures in probe-based confocal laser endomicroscopy Int. J. CARS (IF 3.0) Pub Date : 2024-03-27 Jianzhong You, Serine Ajlouni, Irini Kakaletri, Patra Charalampaki, Stamatia Giannarou
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AI-assisted automatic MRI-based tongue volume evaluation in motor neuron disease (MND) Int. J. CARS (IF 3.0) Pub Date : 2024-03-27 Ina Vernikouskaya, Hans-Peter Müller, Albert C. Ludolph, Jan Kassubek, Volker Rasche
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PitSurgRT: real-time localization of critical anatomical structures in endoscopic pituitary surgery Int. J. CARS (IF 3.0) Pub Date : 2024-03-25 Zhehua Mao, Adrito Das, Mobarakol Islam, Danyal Z. Khan, Simon C. Williams, John G. Hanrahan, Anouk Borg, Neil L. Dorward, Matthew J. Clarkson, Danail Stoyanov, Hani J. Marcus, Sophia Bano
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AIxSuture: vision-based assessment of open suturing skills Int. J. CARS (IF 3.0) Pub Date : 2024-03-25
Abstract Purpose Efficient and precise surgical skills are essential in ensuring positive patient outcomes. By continuously providing real-time, data driven, and objective evaluation of surgical performance, automated skill assessment has the potential to greatly improve surgical skill training. Whereas machine learning-based surgical skill assessment is gaining traction for minimally invasive techniques
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Deep learning-based automatic pipeline for 3D needle localization on intra-procedural 3D MRI Int. J. CARS (IF 3.0) Pub Date : 2024-03-23
Abstract Purpose Accurate and rapid needle localization on 3D magnetic resonance imaging (MRI) is critical for MRI-guided percutaneous interventions. The current workflow requires manual needle localization on 3D MRI, which is time-consuming and cumbersome. Automatic methods using 2D deep learning networks for needle segmentation require manual image plane localization, while 3D networks are challenged
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SF-TMN: SlowFast temporal modeling network for surgical phase recognition Int. J. CARS (IF 3.0) Pub Date : 2024-03-21 Bokai Zhang, Mohammad Hasan Sarhan, Bharti Goel, Svetlana Petculescu, Amer Ghanem
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Near-real-time Mueller polarimetric image processing for neurosurgical intervention Int. J. CARS (IF 3.0) Pub Date : 2024-03-19 Stefano Moriconi, Omar Rodríguez-Núñez, Romain Gros, Leonard A. Felger, Theoni Maragkou, Ekkehard Hewer, Angelo Pierangelo, Tatiana Novikova, Philippe Schucht, Richard McKinley
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Model guided medicine and the search for truth Int. J. CARS (IF 3.0) Pub Date : 2024-03-18 Heinz U. Lemke
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Anatomical attention can help to segment the dilated pancreatic duct in abdominal CT Int. J. CARS (IF 3.0) Pub Date : 2024-03-18 Chen Shen, Holger R. Roth, Yuichiro Hayashi, Masahiro Oda, Gen Sato, Tadaaki Miyamoto, Daniel Rueckert, Kensaku Mori
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3D magnetic seed localization for augmented reality in surgery Int. J. CARS (IF 3.0) Pub Date : 2024-03-16 Pierre Ambrosini, Sara AzizianAmiri, Eliane Zeestraten, Tessa van Ginhoven, Ricardo Marroquim, Theo van Walsum
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PELE scores: pelvic X-ray landmark detection with pelvis extraction and enhancement Int. J. CARS (IF 3.0) Pub Date : 2024-03-15
Abstract Purpose Pelvic X-ray (PXR) is widely utilized in clinical decision-making associated with the pelvis, the lower part of the trunk that supports and balances the trunk. In particular, PXR-based landmark detection facilitates downstream analysis and computer-assisted diagnosis and treatment of pelvic diseases. Although PXR has the advantages of low radiation and reduced cost compared to computed
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Test-time augmentation with synthetic data addresses distribution shifts in spectral imaging Int. J. CARS (IF 3.0) Pub Date : 2024-03-14 Ahmad Bin Qasim, Alessandro Motta, Alexander Studier-Fischer, Jan Sellner, Leonardo Ayala, Marco Hübner, Marc Bressan, Berkin Özdemir, Karl Friedrich Kowalewski, Felix Nickel, Silvia Seidlitz, Lena Maier-Hein
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Cross-sectional angle prediction of lipid-rich and calcified tissue on computed tomography angiography images Int. J. CARS (IF 3.0) Pub Date : 2024-03-13
Abstract Purpose The assessment of vulnerable plaque characteristics and distribution is important to stratify cardiovascular risk in a patient. Computed tomography angiography (CTA) offers a promising alternative to invasive imaging but is limited by the fact that the range of Hounsfield units (HU) in lipid-rich areas overlaps with the HU range in fibrotic tissue and that the HU range of calcified
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Automatic hip osteoarthritis grading with uncertainty estimation from computed tomography using digitally-reconstructed radiographs Int. J. CARS (IF 3.0) Pub Date : 2024-03-12 Masachika Masuda, Mazen Soufi, Yoshito Otake, Keisuke Uemura, Sotaro Kono, Kazuma Takashima, Hidetoshi Hamada, Yi Gu, Masaki Takao, Seiji Okada, Nobuhiko Sugano, Yoshinobu Sato
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Surgical-DINO: adapter learning of foundation models for depth estimation in endoscopic surgery Int. J. CARS (IF 3.0) Pub Date : 2024-03-08 Beilei Cui, Mobarakol Islam, Long Bai, Hongliang Ren
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Assistance by adaptative damping on a complex bimanual task in laparoscopic surgery Int. J. CARS (IF 3.0) Pub Date : 2024-03-07 A. Nassar, F. Vérité, F. Pechereau, M. A. Vitrani
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The distinct roles of reinforcement learning between pre-procedure and intra-procedure planning for prostate biopsy Int. J. CARS (IF 3.0) Pub Date : 2024-03-07 Iani J. M. B. Gayo, Shaheer U. Saeed, Ester Bonmati, Dean C. Barratt, Matthew J. Clarkson, Yipeng Hu
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OCT-based intra-cochlear imaging and 3D reconstruction: ex vivo validation of a robotic platform Int. J. CARS (IF 3.0) Pub Date : 2024-03-04
Abstract Purpose The small size of the cochlea, and its location deeply embedded in thick temporal bone, poses a challenge for intra-cochlear guidance and diagnostics. Current radiological imaging techniques are not able to visualize the cochlear microstructures in detail. Rotational optical coherence tomography (OCT) fibers show great potential for intra-cochlear guidance. The generated images could
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Thickness and design features of clinical cranial implants—what should automated methods strive to replicate? Int. J. CARS (IF 3.0) Pub Date : 2024-03-02 Z. Fishman, James G. Mainprize, Glenn Edwards, Oleh Antonyshyn, Michael Hardisty, C. M. Whyne
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Subtracting–adding strategy for necrotic lesion segmentation in osteonecrosis of the femoral head Int. J. CARS (IF 3.0) Pub Date : 2024-03-02 Jiping Zhang, Sijia Guo, Degang Yu, Cheng-Kung Cheng
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Path tracking control of a steerable catheter in transcatheter cardiology interventions Int. J. CARS (IF 3.0) Pub Date : 2024-02-22 Xiu Zhang, Aditya Sridhar, Xuan Thao Ha, Syed Zain Mehdi, Andrea Fortuna, Mattia Magro, Angela Peloso, Anna Bicchi, Mouloud Ourak, Andrea Aliverti, Emiliano Votta, Emmanuel Vander Poorten, Elena De Momi
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Improved segmentation of basal ganglia from MR images using convolutional neural network with crossover-typed skip connection Int. J. CARS (IF 3.0) Pub Date : 2024-03-01 Takaaki Sugino, Taichi Kin, Nobuhito Saito, Yoshikazu Nakajima
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Generative pretrained transformer-4, an artificial intelligence text predictive model, has a high capability for passing novel written radiology exam questions Int. J. CARS (IF 3.0) Pub Date : 2024-02-21 Avnish Sood, Nina Mansoor, Caroline Memmi, Magnus Lynch, Jeremy Lynch
Purpose AI-image interpretation, through convolutional neural networks, shows increasing capability within radiology. These models have achieved impressive performance in specific tasks within controlled settings, but possess inherent limitations, such as the inability to consider clinical context. We assess the ability of large language models (LLMs) within the context of radiology specialty exams
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Automatic image registration on intraoperative CBCT compared to Surface Matching registration on preoperative CT for spinal navigation: accuracy and workflow Int. J. CARS (IF 3.0) Pub Date : 2024-02-20 Henrik Frisk, Gustav Burström, Oscar Persson, Victor Gabriel El-Hajj, Luisa Coronado, Susanne Hager, Erik Edström, Adrian Elmi-Terander
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Detection support of lesions in patients with prostate cancer using $${}_{{}}^{18} {\text{F}}$$ -PSMA 1007 PET/CT Int. J. CARS (IF 3.0) Pub Date : 2024-02-08 Naoki Tsuchiya, Koichiro Kimura, Ukihide Tateishi, Tadashi Watabe, Koji Hatano, Motohide Uemura, Norio Nonomura, Akinobu Shimizu
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Stereo matching of binocular laparoscopic images with improved densely connected neural architecture search Int. J. CARS (IF 3.0) Pub Date : 2024-01-30
Abstract Purpose Stereo matching is a crucial technology in the binocular laparoscopic-based surgical navigation systems. In recent years, neural networks have been widely applied to stereo matching and demonstrated outstanding performance. however, this method heavily relies on manual feature engineering meaning that professionals must be involved in the feature extraction and matching. This process
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Hybrid representation-enhanced sampling for Bayesian active learning in musculoskeletal segmentation of lower extremities Int. J. CARS (IF 3.0) Pub Date : 2024-01-29 Ganping Li, Yoshito Otake, Mazen Soufi, Masashi Taniguchi, Masahide Yagi, Noriaki Ichihashi, Keisuke Uemura, Masaki Takao, Nobuhiko Sugano, Yoshinobu Sato
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Surgical phase and instrument recognition: how to identify appropriate dataset splits Int. J. CARS (IF 3.0) Pub Date : 2024-01-29 Georgii Kostiuchik, Lalith Sharan, Benedikt Mayer, Ivo Wolf, Bernhard Preim, Sandy Engelhardt
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Design criteria for AI-based IT systems Int. J. CARS (IF 3.0) Pub Date : 2024-01-25 Heinz U. Lemke, Franziska Mathis-Ullrich
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CACTUSS: Common Anatomical CT-US Space for US examinations Int. J. CARS (IF 3.0) Pub Date : 2024-01-25 Yordanka Velikova, Walter Simson, Mohammad Farid Azampour, Philipp Paprottka, Nassir Navab
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Assessment of resectability of pancreatic cancer using novel immersive high-performance virtual reality rendering of abdominal computed tomography and magnetic resonance imaging Int. J. CARS (IF 3.0) Pub Date : 2024-01-22 Julia Madlaina Kunz, Peter Maloca, Andreas Allemann, David Fasler, Savas Soysal, Silvio Däster, Marko Kraljević, Gulbahar Syeda, Benjamin Weixler, Christian Nebiker, Vincent Ochs, Raoul Droeser, Harriet Louise Walker, Martin Bolli, Beat Müller, Philippe Cattin, Sebastian Manuel Staubli
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BDIS-SLAM: a lightweight CPU-based dense stereo SLAM for surgery Int. J. CARS (IF 3.0) Pub Date : 2024-01-19
Abstract Purpose Common dense stereo simultaneous localization and mapping (SLAM) approaches in minimally invasive surgery (MIS) require high-end parallel computational resources for real-time implementation. Yet, it is not always feasible since the computational resources should be allocated to other tasks like segmentation, detection, and tracking. To solve the problem of limited parallel computational
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Pose-based tremor type and level analysis for Parkinson’s disease from video Int. J. CARS (IF 3.0) Pub Date : 2024-01-18 Haozheng Zhang, Edmond S. L. Ho, Xiatian Zhang, Silvia Del Din, Hubert P. H. Shum