Deep-Learning-Based Cerebral Artery Semantic Segmentation in Neurosurgical Operating Microscope Vision Using Indocyanine Green Fluorescence Videoangiography

Machine Learning in Neurosurgery: Toward Complex Inputs, Actionable Predictions, and Generalizable Translations

Machine learning can predict neurosurgical diagnosis and outcomes, power imaging analysis, and perform robotic navigation and tumor labeling. State-of-the-art models can reconstruct and generate images, predict surgical events from video, and assist in intraoperative decision-making. In this review, we will detail the neurosurgical applications of machine learning, ranging from simple to advanced models, and their potential to transform patient care. As machine learning techniques, outputs, and methods become increasingly complex, their performance is often more impactful yet increasingly difficult to evaluate. We aim to introduce these advancements to the neurosurgical audience while suggesting major potential roadblocks to their safe and effective translation. Unlike the previous generation of machine learning in neurosurgery, the safe translation of recent advancements will be contingent on neurosurgeons' involvement in model development and validation.

Single Quasi-Symmetrical LED with High Intensity and Wide Beam Width Using Diamond-Shaped Mirror Refraction Method for Surgical Fluorescence Microscope Applications

To remove tumors with the same blood vessel color, observation is performed using a surgical microscope through fluorescent staining. Therefore, surgical microscopes use light emitting diode (LED) emission and excitation wavelengths to induce fluorescence emission wavelengths. LEDs used in hand-held type microscopes have a beam irradiation range of 10° and a weak power of less than 0.5 mW. Therefore, fluorescence emission is difficult. This study proposes to increase the beam width and power of LED by utilizing the quasi-symmetrical beam irradiation method. Commercial LED irradiates a beam 1/r2 distance away from the target (working distance). To obtain the fluorescence emission probability, set up four mirrors. The distance between the mirrors and the LED is 5.9 cm, and the distance between the mirrors and the target is 2.95 cm. The commercial LED reached power on target of 8.0 pW within the wavelength band of 405 nm. The power reaching the target is 0.60 mW in the wavelength band of 405 nm for the LED with the beam mirror attachment method using the quasi-symmetrical beam irradiation method. This result is expected to be sufficient for fluorescence emission. The light power of the mirror was increased by approximately four times.