AI Medical Compendium Topic

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Surgery, Computer-Assisted

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Artificial Intelligence, Radiomics, and Computational Modeling in Skull Base Surgery.

Advances in experimental medicine and biology
This chapter explores current artificial intelligence (AI), radiomics, and computational modeling applications in skull base surgery. AI advancements are providing opportunities to improve diagnostic accuracy, surgical planning, and postoperative car...

Machine and Deep Learning in Hyperspectral Fluorescence-Guided Brain Tumor Surgery.

Advances in experimental medicine and biology
Malignant glioma resection is often the first line of treatment in neuro-oncology. During glioma surgery, the discrimination of tumor's edges can be challenging at the infiltration zone, even by using surgical adjuncts such as fluorescence guidance (...

[Overview of Key Technologies in Surgical Robots and Optimization Discussions].

Zhongguo yi liao qi xie za zhi = Chinese journal of medical instrumentation
Surgical robot is the national strategic diagnostic and therapeutic equipment research focus, get a number of scientific research institutes, colleges and universities and enterprises pay extensive attention to the design and development of a variety...

Robotic navigation with deep reinforcement learning in transthoracic echocardiography.

International journal of computer assisted radiology and surgery
PURPOSE: The search for heart components in robotic transthoracic echocardiography is a time-consuming process. This paper proposes an optimized robotic navigation system for heart components using deep reinforcement learning to achieve an efficient ...

Deep learning-enabled fluorescence imaging for surgical guidance: training for oral cancer depth quantification.

Journal of biomedical optics
SIGNIFICANCE: Oral cancer surgery requires accurate margin delineation to balance complete resection with post-operative functionality. Current fluorescence imaging systems provide two-dimensional margin assessment yet fail to quantify tumor depth p...

[Influencing factors of implant accuracy of oral implant robot].

Zhonghua kou qiang yi xue za zhi = Zhonghua kouqiang yixue zazhi = Chinese journal of stomatology
In recent years, robots have been gradually applied in the field of oral implantation. Compared with static guide and dynamic navigation, robot-assisted implant surgery has the characteristics of high precision, high stability and high safety, but th...

Automatic Landmark Detection for Preoperative Planning of High Tibial Osteotomy Using Traditional Feature Extraction and Deep Learning Methods.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: Automatic High Tibial Osteotomy (HTO) landmark detection methods promise to improve the effectiveness and standardisation of HTO preoperative planning. Unfortunately, due to the limited number of HTO datasets, existing methods are less ro...

Target-specified reference-based deep learning network for joint image deblurring and resolution enhancement in surgical zoom lens camera calibration.

Computers in biology and medicine
BACKGROUND AND OBJECTIVE: For the augmented reality of surgical navigation, which overlays a 3D model of the surgical target on an image, accurate camera calibration is imperative. However, when the checkerboard images for calibration are captured us...

Accuracy of Zygomatic Implant Placement Using Task-Autonomous Robotic System or Dynamic Navigation: An In Vitro Study.

Clinical oral implants research
OBJECTIVES: To evaluate and compare the accuracy of task-autonomous robot-assisted implant surgery (RAIS) and dynamic computer-assisted implant surgery (dCAIS) for zygomatic implant placement.