arXiv subjects

Fangjie Li

Publications and source records attributed to Fangjie Li.

6 recordsLinked to original sources

arXiv2026

Automated Assessment of Kidney Ureteroscopy Exploration for Training

Purpose: Kidney ureteroscopic navigation is challenging with a steep learning curve. However, current clinical training has major deficiencies, as it requires one-on-one feedback from experts and occurs in the operating room (OR). Therefore, there is a need for a phantom training system with automated feedback to greatly \revision{expand} training opportunities. Methods: We propose a novel, purely ureteroscope video-based scope localization framework that automatically identifies calyces missed by the trainee in a phantom kidney exploration. We use a slow, thorough, prior exploration video of the kidney to generate a reference reconstruction. Then, this reference reconstruction can be used to localize any exploration video of the same phantom. Results: In 15 exploration videos, a total of 69 out of 74 calyces were correctly classified. We achieve < 4mm camera pose localization error. Given the reference reconstruction, the system takes 10 minutes to generate the results for a typical exploration (1-2 minute long). Conclusion: We demonstrate a novel camera localization framework that can provide accurate and automatic feedback for kidney phantom explorations. We show its ability as a valid tool that enables out-of-OR training without requiring supervision from an expert.

eess.IV↗

arXiv2025

Augmented Reality-based Guidance with Deformable Registration in Head and Neck Tumor Resection

Head and neck squamous cell carcinoma (HNSCC) has one of the highest rates of recurrence cases among solid malignancies. Recurrence rates can be reduced by improving positive margins localization. Frozen section analysis (FSA) of resected specimens is the gold standard for intraoperative margin assessment. However, because of the complex 3D anatomy and the significant shrinkage of resected specimens, accurate margin relocation from specimen back onto the resection site based on FSA results remains challenging. We propose a novel deformable registration framework that uses both the pre-resection upper surface and the post-resection site of the specimen to incorporate thickness information into the registration process. The proposed method significantly improves target registration error (TRE), demonstrating enhanced adaptability to thicker specimens. In tongue specimens, the proposed framework improved TRE by up to 33% as compared to prior deformable registration. Notably, tongue specimens exhibit complex 3D anatomies and hold the highest clinical significance compared to other head and neck specimens from the buccal and skin. We analyzed distinct deformation behaviors in different specimens, highlighting the need for tailored deformation strategies. To further aid intraoperative visualization, we also integrated this framework with an augmented reality-based auto-alignment system. The combined system can accurately and automatically overlay the deformed 3D specimen mesh with positive margin annotation onto the resection site. With a pilot study of the AR guided framework involving two surgeons, the integrated system improved the surgeons' average target relocation error from 9.8 cm to 4.8 cm.

eess.IV↗

arXiv2025

PERSEUS: Perception with Semantic Endoscopic Understanding and SLAM

Purpose: Natural orifice surgeries minimize the need for incisions and reduce the recovery time compared to open surgery; however, they require a higher level of expertise due to visualization and orientation challenges. We propose a perception pipeline for these surgeries that allows semantic scene understanding. Methods: We bring learning-based segmentation, depth estimation, and 3D reconstruction modules together to create real-time segmented maps of the surgical scenes. Additionally, we use registration with robot poses to solve the scale ambiguity of mapping from monocular images, and allow the use of semantically informed real-time reconstructions in robotic surgeries. Results: We achieve sub-milimeter reconstruction accuracy based on average one-sided Chamfer distances, average pose registration RMSE of 0.9 mm, and an estimated scale within 2% of ground truth. Conclusion: We present a modular perception pipeline, integrating semantic segmentation with real-time monocular SLAM for natural orifice surgeries. This pipeline offers a promising solution for scene understanding that can facilitate automation or surgeon guidance.

cs.RO↗

arXiv2025

From Monocular Vision to Autonomous Action: Guiding Tumor Resection via 3D Reconstruction

Surgical automation requires precise guidance and understanding of the scene. Current methods in the literature rely on bulky depth cameras to create maps of the anatomy, however this does not translate well to space-limited clinical applications. Monocular cameras are small and allow minimally invasive surgeries in tight spaces but additional processing is required to generate 3D scene understanding. We propose a 3D mapping pipeline that uses only RGB images to create segmented point clouds of the target anatomy. To ensure the most precise reconstruction, we compare different structure from motion algorithms' performance on mapping the central airway obstructions, and test the pipeline on a downstream task of tumor resection. In several metrics, including post-procedure tissue model evaluation, our pipeline performs comparably to RGB-D cameras and, in some cases, even surpasses their performance. These promising results demonstrate that automation guidance can be achieved in minimally invasive procedures with monocular cameras. This study is a step toward the complete autonomy of surgical robots.

cs.CV↗

arXiv2024

Invariant neuromorphic representations of tactile stimuli improve robustness of a real-time texture classification system

Humans have an exquisite sense of touch which robotic and prosthetic systems aim to recreate. We developed algorithms to create neuron-like (neuromorphic) spiking representations of texture that are invariant to the scanning speed and contact force applied in the sensing process. The spiking representations are based on mimicking activity from mechanoreceptors in human skin and further processing up to the brain. The neuromorphic encoding process transforms analog sensor readings into speed and force invariant spiking representations in three sequential stages: the force invariance module (in the analog domain), the spiking activity encoding module (transforms from analog to spiking domain), and the speed invariance module (in the spiking domain). The algorithms were tested on a tactile texture dataset collected in 15 speed-force conditions. An offline texture classification system built on the invariant representations has higher classification accuracy, improved computational efficiency, and increased capability to identify textures explored in novel speed-force conditions. The speed invariance algorithm was adapted to a real-time human-operated texture classification system. Similarly, the invariant representations improved classification accuracy, computational efficiency, and capability to identify textures explored in novel conditions. The invariant representation is even more crucial in this context due to human imprecision which seems to the classification system as a novel condition. These results demonstrate that invariant neuromorphic representations enable better performing neurorobotic tactile sensing systems. Furthermore, because the neuromorphic representations are based on biological processing, this work can be used in the future as the basis for naturalistic sensory feedback for upper limb amputees.

cs.RO↗

arXiv2018

Alternative Interpretation of Lens Aberration on OTF

This paper demonstrates a method of interpreting the mechanism of aberration of optical systems based on non-Fourier transform optical transfer function (OTF). According to the parameters of object plane cosine fringe, we obtain the position on the pupil plane of the two beams of the interference pair emitted by the cosine fringes. By combining the aberrations of the lens, the phase of the cosine fringe of each interference pair in the image plane can be obtained. Then the intensity of the cosine fringe formed by all the interference pattern is superimposed to obtain the brightness distribution of the cosine fringe on the image plane. After that, the OTF of the aberration system can be obtained on the basis of the cosine fringe modulation on the image plane and the phase shift. Finally, taking the non-Fourier transform OTF theory with wave analyze the complex optical system, providing help for the optical system design and imaging quality evaluation.

physics.optics↗