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检索条件"任意字段=Conference on Medical Imaging - Image-Guided Procedures, Robotic Interventions and Modeling"

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Real-time guidewire tracking and segmentation in intraoperative X-ray

Real-time guidewire tracking and segmentation in intraoperat...

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conference on medical imaging - image-guided procedures, robotic interventions, and modeling

作者： Zhang, Baochang Bui, Mai Wang, Cheng Bourier, Felix Schunkert, Heribert Navab, Nassir Tech Univ Munich Munich Germany German Heart Ctr Munich Munich Germany ZhongDa Hosp Southeast Univ Nanjing Peoples R China DZHK German Ctr Cardiovasc Res Munich Heart Alliance Munich Germany Munich Inst Robot & Machine Intelligence MIRMI Munich Germany

ISBN: (纸本)9781510649446;9781510649439

During endovascular interventions, physicians have to perform accurate and immediate operations based on the available real-time information, such as the shape and position of guidewires observed on the fluoroscopic images, haptic information and the patients' physiological signals. For this purpose, real-time and accurate guidewire segmentation and tracking can enhance the visualization of guidewires and provide visual feedback for physicians during the intervention as well as for robot-assisted interventions. Nevertheless, this task often comes with the challenge of elongated deformable structures that present themselves with low contrast in the noisy fluoroscopic image sequences. To address these issues, a two-stage deep learning framework for real-time guidewire segmentation and tracking is proposed. In the first stage, a Yolov5s detector is trained, using the original X-ray images as well as synthetic ones, which is employed to output the bounding boxes of possible target guidewires. More importantly, a refinement module based on spatiotemporal constraints is incorporated to robustly localize the guidewire and remove false detections. In the second stage, a novel and efficient network is proposed to segment the guidewire in each detected bounding box. The network contains two major modules, namely a hessian-based enhancement embedding module and a dual self-attention module. Quantitative and qualitative evaluations on clinical intra-operative images demonstrate that the proposed approach significantly outperforms our baselines as well as the current state of the art and, in comparison, shows higher robustness to low quality images.

关键词： Guidewire segmentation guidewire tracking X-ray imaging

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Segmentation of the mouse skull for MRI guided transcranial focused ultrasound therapy planning

Segmentation of the mouse skull for MRI guided transcranial ...

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conference on medical imaging - image-guided procedures, robotic interventions, and modeling

作者： Hopp, T. Springer, L. Gross, C. Grudzenski-Theis, S. Mathis-Ullrich, F. Ruiter, N., V Karlsruhe Inst Technol Inst Data Proc & Elect Karlsruhe Germany Heidelberg Univ Karlsruhe Inst Technol KIT HEiKA Heidelberg Karlsruhe Strateg Partnership Heidelberg Germany Heidelberg Univ Univ Med Mannheim Dept Neurol Heidelberg Germany Karlsruhe Inst Technol Inst Anthropomat & Robot Karlsruhe Germany

ISBN: (纸本)9781510649446;9781510649439

For opening the blood brain barrier using focused ultrasound (FUS) to treat neurodegenerative diseases, mouse-specific therapy planning is an essential step. For our therapy planning approach based on acoustic simulations we here propose to automatically segment the mouse skull and brain from magnetic resonance imaging, which is usually used in combination with FUS for monitoring purposes. The proposed method consists of (1) pre-processing to enhance the image contrast and remove noise, (2) a rough skull segmentation using morphological operations and adaptive binarization, (3) segmentation of the brain using the established 3D-PCNN method, (4) correction of the skull segmentation using the anatomical information about the brain location and (5) a post-processing to remove obvious errors from the final skull segmentation. The method is evaluated with four in-vivo datasets obtained with different parameters. The median Matthews Correlation Coefficient (MCC) on all slices of four datasets was 0.85 for the brain segmentation, 0.69 for the overall skull segmentation and 0.78 for the skull cap. Finally for showcasing the application an acoustic simulation based on the segmentation is presented, which results in a comparable prediction of the pressure field prediction as our earlier method based on micro-CT, and lines up well with literature estimations of the ultrasound attenuation.

关键词： Skull segmentation magnetic resonance imaging subject-specific therapy planning focused ultrasound blood brain barrier opening

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Automatic, Deep-Learning-Based Segmentation of the Amygdalohippocampectomy Resection Cavity in MR images

Automatic, Deep-Learning-Based Segmentation of the Amygdaloh...

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medical imaging 2023: image-guided procedures, robotic interventions, and modeling

作者： Su, Dingjie Paulo, Danika L. Tyler, Ball Morgan, Victoria L. Englot, Dario J. Dawant, Benoit M. Vanderbilt University Department of Computer Science NashvilleTN37235 United States Vanderbilt University Department of Electrical and Computer Engineering NashvilleTN37235 United States NashvilleTN37232 United States Vanderbilt University Medical Center Department of Neurological Surgery NashvilleTN37232 United States

ISBN: (纸本)9781510660373

Selective amygdalohippocampectomy (SelAH) for mesial temporal lobe epilepsy (mTLE) involves the resection of the anterior hippocampus and the amygdala. A recent study related to SelAH reports that among 168 patients for whom two-year Engel outcomes data were available, 73% had Engel 1 outcomes (free of disabling seizure);16.6% had Engel II outcomes (rare disabling seizures);4.7% had Engel III outcomes (worthwhile improvement);and 5.3% had Engel IV outcomes (no worthwhile improvement). Success rate among sites also varies greatly. Possible explanations for variability in outcomes are the resected volume and/or the subregion of the hippocampus and amygdala that have been resected. To explore this hypothesis, the accurate segmentation of the resected cavity needs to be performed on a large scale. This is, however, a difficult and time-consuming task that requires expertise. Here we explore using a nnUNET to perform the task. Inspired by Youngeun [15], a level set loss is used in addition to the original DICE and cross-entropy loss in nnUNET to capture the cavity boundaries better. We show that, even with a modest-sized training set (25 volumes), the median DICE value between automated and manual segmentations is 0.88, which suggests that the automatic and accurate segmentation of the resection cavity is achievable. © 2023 SPIE.

关键词： Magnetic resonance imaging

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Tumor deformation correction for an image guidance system in breast conserving surgery

Tumor deformation correction for an image guidance system in...

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conference on medical imaging - image-guided procedures, robotic interventions, and modeling

作者： Richey, Winona L. Heiselman, Jon Ringel, Morgan Meszoely, Ingrid M. Miga, Michael, I Vanderbilt Univ Dept Biomed Engn Nashville TN 37235 USA Vanderbilt Univ Div Surg Oncol Med Ctr Nashville TN USA Vanderbilt Univ Dept Radiol & Radiol Sci Nashville TN USA Vanderbilt Inst Surg & Engn Nashville TN USA Vanderbilt Univ Dept Neurol Surg Med Ctr Nashville TN USA

ISBN: (纸本)9781510649446;9781510649439

Breast cancer is the most common cancer in women, and surgical resection is standard of care for the majority of breast cancer patients. Unfortunately, current reoperation rates are 10-29%. Uncertainty in lesion localization is one of the main factors contributing to these high reoperation rates. This work uses the linearized iterative boundary reconstruction approach to model patient breast deformation due to abduction of the ipsilateral arm. A preoperative supine magnetic resonance (MR) image was obtained with the patient's arms down near the torso. A mock intraoperative breast shape was measured from a supine MR image obtained with the patient's arm up near the head. Sparse data was subsampled from the full volumetric image to represent realistic intraoperative data collection: surface fiducial points, the intra-fiducial skin surface, and the chest wall as measured with 7 tracked ultrasound images. The deformed preoperative arm-down data was compared to the ground truth arm-up data. From rigid registration to model correction the tumor centroid distance improves from 7.3 mm to 3.3 mm, average surface fiducial error across 9 synthetic fiducials and the nipple improves from 7.4. 2.2 to 1.3. 0.7, and average subsurface error across 14 corresponding features improves from 6.2 +/- 1.4 mm to 3.5 +/- 1.1 mm. Using preoperative supine MR imaging and sparse data in the deformed position, this modeling framework can correct for breast shape changes between imaging and surgery to more accurately predict intraoperative position of the tumor as well as 10 surface fiducials and 14 subsurface features.

关键词： breast conserving surgery image-guided surgery soft tissue deformation breast cancer lumpectomy registration biomechanical modeling

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Respiratory motion control during stereotactic thermal ablation of malignant liver tumors - clinical solutions to a technical problem

Respiratory motion control during stereotactic thermal ablat...

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medical imaging 2025: image-guided procedures, robotic interventions, and modeling

作者： Paolucci, Iwan Albuquerque Marques Silva, Jessica Jones, Kyle A. Ruiz, Joseph Jackson, Timothy Wang, Mi Brock, Kristy K. Tan, Jens Odisio, Bruno C. Department of Interventional Radiology The University of Texas MD Anderson Cancer Center Houston TX United States Department of Imaging Physics The University of Texas MD Anderson Cancer Center Houston TX United States Department of Anesthesiology and Perioperative Medicine The University of Texas MD Anderson Cancer Center Houston TX United States

ISBN: (纸本)9781510685949

Percutaneous thermal ablation is a minimally invasive treatment option for select liver tumors. Stereotactic guidance for percutaneous thermal ablation depends on reliable respiratory motion control to maintain a consistent liver location and shape throughout the procedure for image acquisition and ablation probe placements. This is necessary to achieve accurate ablation probe placement and improve pre- to post-ablation image fusion for ablative margin assessment. In this prospective registry-based study, patients undergoing stereotactic percutaneous thermal ablation at a large academic cancer center in the United States between June 2023 and August 2024 were included. We compare lateral targeting errors between three subsequently introduced respiratory motion control techniques and investigated the influence of body mass index (BMI) on lateral targeting errors. In addition, we compare overall organ motion and deformation between intraprocedure pre- and post-ablation CT imaging using a biomechanical deformable image registration technique. We showed that High frequency jet ventilation resulted in higher targeting accuracy (3.7mm vs. 5.6 mm;p = 0.029) and mitigated the influence of BMI (r = -0.27 vs. r = 0.28) compared to breath holds with and without end tidal CO₂ monitoring. Overall organ deformation between pre- and post-ablation CT imaging was not significantly reduced compared to breath holds (0.29 cm vs. 0.32 cm, p = 0.25). High frequency jet ventilation is the preferred option for respiratory motion control during stereotactic percutaneous thermal ablation of liver tumors. However, deformable image registration is still necessary for most cases for accurate assessment of sufficient ablative margins. © 2025 SPIE

关键词： liver liver tumors respiratory motion control stereotactic image guidance Thermal ablation

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Novel view synthesis using neural radiance fields for laparoscopic surgery navigation

Novel view synthesis using neural radiance fields for laparo...

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medical imaging 2025: image-guided procedures, robotic interventions, and modeling

作者： Nawawithan, Nati Yu, James Pruitt, Kelden Fei, Baowei Center for Imaging and Surgical Innovation University of Texas at Dallas Richardson TX United States Department of Bioengineering University of Texas at Dallas Richardson TX United States Department of Radiology University of Texas Southwestern Medical Center Dallas TX United States

ISBN: (纸本)9781510685949

Laparoscopic surgery is a widely used minimally invasive technique to treat a variety of pathologies within the abdominopelvic region. Compared to conventional open surgery, laparoscopic surgery reduces iatrogenic trauma and hospital stay length. Nevertheless, surgeons have a limited field of view during operation because surgical instruments are inserted through the patient's body via small incisions. To improve surgeon's perception, surgical navigation techniques are implemented to improve visualization. A number of surgical navigation systems being developed are integrated with computer algorithms to enhance their efficiency. In this work, we generate novel views, depths, and camera poses of corresponding laparoscopic images to augment our dataset, which can then be used to train and evaluate learning-based computer vision algorithms such as simultaneous localization and mapping (SLAM) and visual odometry. Our existing dataset was generated from porcine tissue images using a laparoscope and an optical tracking system to capture camera poses. We performed tissue surface reconstruction of the dataset via the NeRF-SLAM algorithm. Camera poses were transformed to acquire novel views of RGB laparoscopic images and their corresponding depth images. The results show that the simulated RGB images have an average peak signal-to-noise ratios (PSNR) between 29.17-29.79 dB, structural similarity index measure (SSIM) value between 0.6061-0.6174, and learned perceptual image patch similarity (LPIPS) value between 0.568-0.592 compared to the corresponding input images. This work provides a foundation for the generation of synthetic datasets, which could be useful for learning-based autonomous surgical navigation systems. © 2025 SPIE

关键词： image-guided intervention Laparoscopic surgery neural radiance fields

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Personalized Antenna Pathways for Enhancing Safety and Efficacy: Optimizing Microwave Ablation Outcomes in Hepatic Tumor Treatments

Personalized Antenna Pathways for Enhancing Safety and Effic...

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medical imaging 2025: image-guided procedures, robotic interventions, and modeling

作者： Heshmat, Amirreza Tino, Rance Albuquerque Marques Silva, Jessica Paolucci, Iwan Koay, Eugene J. Jones, Kyle A. Odisio, Bruno C. Brock, Kristy K. Department of Imaging Physics The University of Texas MD Anderson Cancer Center Houston TX United States Department of Gastrointestinal Radiation Oncology The University of Texas MD Anderson Cancer Center Houston TX United States Department of Interventional Radiology The University of Texas MD Anderson Cancer Center Houston TX United States

ISBN: (纸本)9781510685949

Microwave ablation (MWA) is a minimally invasive technique for treating malignant liver tumors. Achieving an adequate minimal ablative margin (MAM) of at least 5 mm prevents tumor progression and recurrence. However, challenges in consistently achieving adequate MAM due to factors such as tumor morphology and location, antenna placement, and procedural complications highlight the opportunity for optimized insertion pathway techniques to improve outcomes. image data from 10 patients were used to create patient-specific 3D finite element models, including liver, tumor, and vasculature. Simulations were conducted based on a triaxial antenna at 2.45 GHz for an ablation time of 10 minutes and mimicked clinical procedure parameters. The investigation of two clinically feasible antenna pathways was guided using incremental probe rotations and collision detection algorithms to evaluate potential pathways. These pathways were selected based on their ability to minimize collisions with critical structures, including liver vasculature, lung, heart, rib cage, pancreas, gallbladder, and bowels. The chosen pathways were analyzed for their potential to reduce ablated tissue effectively, achieving reductions between 4.5% and 44% while maintaining adequate MAM without compromising the effectiveness of MWA. This study emphasizes the potential clinical impact of optimizing antenna insertion pathways and the critical role of personalized treatment planning in improving the safety and effectiveness of MWA for liver cancer, suggesting the potential for patient-specific 3D simulations to improve clinical outcomes. © 2025 SPIE

关键词： Simulations Ablation Antennas Tumors Liver Tissues 3D modeling Safety Cancer Microwave radiation

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Deformable Motion Compensation for Intraprocedural Vascular Cone-beam CT with Sequential Projection Domain Targeting and Vessel-Enhancing Autofocus

Deformable Motion Compensation for Intraprocedural Vascular ...

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medical imaging 2023: image-guided procedures, robotic interventions, and modeling

作者： Lu, Alexander Huang, Heyuan Hu, Yicheng Zbijewski, Wojtek Unberath, Mathias Siewerdsen, Jeffrey H. Weiss, Clifford R. Sisniega, Alejandro Department of Biomedical Engineering Johns Hopkins University BaltimoreMD United States Department of Computer Science Johns Hopkins University BaltimoreMD United States Departments of Imaging Physics Neurosurgery and Radiation Physics The University of Texas M.D. Anderson Cancer Center TX United States Department of Radiology Johns Hopkins University BaltimoreMD United States

ISBN: (纸本)9781510660373

Purpose: Cone-beam CT (CBCT) is used in interventional radiology (IR) for identification of complex vascular anatomy, difficult to visualize in 2D fluoroscopy. However, long acquisition time makes CBCT susceptible to soft-tissue deformable motion that degrades visibility of fine vessels. We propose a targeted framework to compensate for deformable intra-scan motion via learned full-sequence models for identification of vascular anatomy coupled to an autofocus function specifically tailored to vascular imaging. Methods: The vessel-targeted autofocus acts in two stages: (i) identification of vascular and catheter targets in the projection domain;and, (ii) autofocus optimization for a 4D vector field through an objective function that quantifies vascular visibility. Target identification is based on a deep learning model that operates on the complete sequence of projections, via a transformer encoder-decoder architecture that uses spatial-temporal self-attention modules to infer long-range feature correlations, enabling identification of vascular anatomy with highly variable conspicuity. The vascular autofocus function is derived through eigenvalues of the local image Hessian, which quantify the local image structure for identification of bright tubular structures. Motion compensation was achieved via spatial transformer operators that impart time dependent deformations to NPAR = 90 partial angle reconstructions, allowing for efficient minimization via gradient backpropagation. The framework was trained and evaluated in synthetic abdominal CBCTs obtained from liver MDCT volumes and including realistic models of contrast-enhanced vascularity with 15 to 30 end branches, 1-3.5 mm vessel diameter, and 1400 HU contrast. Results: The targeted autofocus resulted in qualitative and quantitative improvement in vascular visibility in both simulated and clinical intra-procedural CBCT. The transformer-based target identification module resulted in superior detection of target vasc

关键词： Motion compensation

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A 2D/3D US/CT-guided system for percutaneous focal liver thermal ablation

A 2D/3D US/CT-guided system for percutaneous focal liver the...

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conference on medical imaging - image-guided procedures, robotic interventions, and modeling

作者： Xing, Shuwei Cool, Derek W. Gardi, Lori Bax, Jeffrey Chen, Elvis C. S. Peters, Terry M. Fenster, Aaron Western Univ Robarts Res Inst London ON Canada Western Univ Sch Biomed Engn London ON Canada Western Univ Dept Med Biophys London ON Canada Western Univ Dept Med Imaging London ON Canada Lawson Hlth Res Inst London ON Canada

ISBN: (纸本)9781510649446;9781510649439

image-guided percutaneous thermal ablations are promising techniques for the treatment of focal liver tumors. Conventionally, 2D ultrasound (US)-guidance is used extensively to assist liver tumor treatment. Recently, 3D US imaging has attracted much attention as its provided volumetric information can better help physicians interpret and localize liver structures. However, 3D US imaging still has the same limitation as conventional 2D US imaging in visualizing ultrasonically invisible cases. To address this issue, the current mainstream solution is to provide real-time 2D US-CT/MRI registered images by leveraging external tracking systems, such as electromagnetic (EM) or optical approaches. Due to their inevitable constraints, such as the presence of ferromagnetic structures in the case of EM tracking systems, or the line-of-sight limitation for optical systems, whether these solutions can be readily applied to the clinic has been under investigation. In this paper, we aim to investigate the feasibility of a 3D US-based ablation paradigm using our developed 2D/3D US/CT-guided liver ablation system. To achieve this goal and provide accurate guidance for ablation procedures, we proposed a local-and-global calibration method to track our mechatronic guidance arm. We also used a fiducial-based registration method to align 3D US with diagnostic CT images and implemented the re-slicing function to display the CT image corresponding to the US transducer's pose. Results demonstrated the feasibility of our system to visualize the complementary information from multiple image modalities in real time. Our calibration method can provide accurate tracking with an unsigned error of 1.6 mm +/- 0.4 mm. This work is a step towards providing a system to guide the liver ablation procedure, including cases with ultrasonically invisible or poorly visible tumors.

关键词： 3D US percutaneous thermal ablation calibration multimodality registration liver ablation

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A 4D visualization tool for treatment planning of non-invasive radioablation in patients with ventricular tachycardia

A 4D visualization tool for treatment planning of non-invasi...

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medical imaging 2023: image-guided procedures, robotic interventions, and modeling

作者： Haberl, Connor Crean, Andrew M. Lekx-Toniolo, Katie Ali, Elsayed Nery, Pablo B. Nair, Girish M. Cook, Graham Rajabiyazdi, Fateme Redpath, Calum deKemp, Robert Carleton University 1125 Colonel By Dr OttawaONK1S 5B6 Canada University of Ottawa Heart Institute 40 Ruskin St OttawaONK1Y 4W7 Canada The Ottawa Hospital Cancer Centre 501 Smyth Rd OttawaONK1H 8L6 Canada

ISBN: (纸本)9781510660373

Non-invasive cardiac radioablation is an emerging therapy for the treatment of ventricular tachycardia (VT). Electrophysiologic, anatomic and molecular imaging studies are used to localize the breakout region of the VT, but current therapy planning is tedious and prone to error due to a lack of data integration. In this work we present the design and development of a software platform and workflow to facilitate precision-targeted therapy planning, including affine non-rigid multimodality image registration and 2D-3D-4D visualization across modalities. Registration accuracy was measured using Dice Similarity and Hausdorff Distance of total left ventricle tissue volumes, which were 0.914 ± 0.013 and 2.65mm ± 0.34mm, respectively (average ± standard deviation). Electrocardiographic maps of VT parameters were registered temporally to surface electrode data to recreate familiar ECG tracings. 2D polar maps, 3D slice-views, and 4D cine-renderings were used for hybrid fusion displays of molecular and electroanatomic images. Segmentations of the cardiac-gated contrast CT blood-pool and molecular images of perfusion and glucose metabolism were used to identify regions of fibrotic scar tissue and hibernating myocardium in the 3D scene. Ablation targets were painted onto the 2D polar map, 3D slice or 4D-cine views, and exported as DICOM for import to radiotherapy planning software. We anticipate that the combination of accurate multimodality image registration and visualizations will enable more reliable therapy planning, expedite treatment and may improve understanding of the underlying pathophysiology of these lethal arrhythmias. © 2023 SPIE.

关键词： Molecular imaging

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