Single-port transvesical simple prostatectomy for the surgical treatment of benign prostatic hyperplasia: functional and continence outcomes
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Serum PSA and digital rectal examination remain the key diagnostic tools for detecting prostate cancer. However, due to the limited specificity of serum PSA, the applicability of this marker continues to be controversial. Recent use of image-guided biopsy along with pathological assessment and the use of biomarkers has dramatically improved the diagnosis of clinically significant cancer. Despite the two modalities working together for diagnosis biomarker research often fails to correlate findings with imaging.
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Surgical video workflow analysis via visual-language learning
Surgical video workflow analysis has made intensive development in computer-assisted surgery by combining deep learning models, aiming to enhance surgical scene analysis and decision-making. However, previous research has primarily focused on coarse-grained analysis of surgical videos, e.g., phase recognition, instrument recognition, and triplet recognition that only considers relationships within surgical triplets. In order to provide a more comprehensive fine-grained analysis of surgical videos, this work focuses on accurately identifying triplets <instrument, verb, target> from surgical videos. Specifically, we propose a vision-language deep learning framework that incorporates intra- and inter- triplet modeling, termed I2TM, to explore the relationships among triplets and leverage the model understanding of the entire surgical process, thereby enhancing the accuracy and robustness of recognition. Besides, we also develop a new surgical triplet semantic enhancer (TSE) to establish semantic relationships, both intra- and inter-triplets, across visual and textual modalities. Extensive experimental results on surgical video benchmark datasets demonstrate that our approach can capture finer semantics, achieve effective surgical video understanding and analysis, with potential for widespread medical applications.
Compact and reciprocal probe-signal-integrated rotational Doppler velocimetry with fiber-sculpted light
In recent years, with the clarification of the mechanism of the rotational Doppler effect (RDE), there has attracted extensive attention to its development of applications, especially in the detection of the angular velocity of rotating objects. On the other hand, optical fiber technology is widely applied in laser velocimetry from beam delivery to scattered light collection, aiding the miniaturization of instruments. Here we report the first all-fiber rotational Doppler velocimetry (AF-RDV) with a single probe based on a fabricated mode-sculpted fiber-optic element. The constructed AF-RDV can be operated in two reciprocal schemes wherein exchanging the illuminating mode and detected mode. Using this, we experimentally demonstrate the mode-changing dependent nature of the RDE. Particularly, the results suggest that the rotational Doppler shift can be observed by mode-filtering the scattered signal even with a non-twisted probe light. We also show the achromatic property of the RDE by scanning the incident wavelength, enabling the AF-RDV within an ultra-broadband operation range. The AF-RDV exhibits favorable performance for detecting spinning rough surfaces. It may provide an exciting new practical sensing instrument with significant prospects for monitoring angular motion in both research and industry.
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