AIMC Topic: Endoscopy

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SDMFFN: a novel specular detection median filtering fusion network for specular reflection removal in endoscopic images.

Biomedical physics & engineering express
. Endoscopic imaging is vital in Minimally Invasive Surgery (MIS), but its utility is often compromised by specular reflections that obscure important details and hinder diagnostic accuracy. Existing methods to address these reflections face limitati...

Intraoperative use of artificial intelligence (AI) during endoscopic lithotripsy: a systematic review from EAU endourology.

World journal of urology
INTRODUCTION: The current systematic review aims to summarize the existing data on intraoperative use of artificial intelligence (AI) during endoscopic lithotripsy in order to assess which particular applications are feasible and have prospects of wi...

AI-assisted recurrent laryngeal nerve identification during endoscopic/robotic thyroid surgery based on the CMC-UNet model: a multicenter retrospective study.

Journal of robotic surgery
During endoscopic or robotic-assisted thyroid surgery, the field of view may be restricted by tissue swelling or bleeding. These Limitations make delicate surgical manipulation in the confined space more challenging. This study proposes an artificial...

Comprehensive analysis of 55,213 stones: understanding common morphological associations advances endoscopic stone recognition and AI integration.

World journal of urology
PURPOSE: To assess the prevalence and associations of urinary stone morphologies, focusing on their relevance for Endoscopic Stone Recognition and improving AI-assisted ESR (AESR) systems.

Machine learning combine with nomogram to guide the establishment of endoscopic assistant system for gasless transaxillary endoscopic thyroidectomy.

Annals of medicine
OBJECTIVE: To explore the influence related factors of endoscopic assistant in gasless transaxillary endoscopic thyroidectomy by using machine learning and nomogram, and construct an endoscopic assistant system.

Deep learning using nasal endoscopy and T2-weighted MRI for prediction of sinonasal inverted papilloma-associated squamous cell carcinoma: an exploratory study.

European radiology experimental
BACKGROUND: Detecting malignant transformation of sinonasal inverted papilloma (SIP) into squamous cell carcinoma (SIP-SCC) before surgery is a clinical need. We aimed to explore the value of deep learning (DL) that leverages nasal endoscopy and T2-w...

Deep learning-based allergic rhinitis diagnosis using nasal endoscopy images.

Scientific reports
Allergic rhinitis typically has edematous and pale turbinates or erythematous and inflamed turbinates. While traditional approaches include using skin prick tests (SPT) to determine the presence of AR, It is often not related to actual symptoms, and ...

Advancing artificial intelligence applicability in endoscopy through source-agnostic camera signal extraction from endoscopic images.

PloS one
INTRODUCTION: Successful application of artificial intelligence (AI) in endoscopy requires effective image processing. Yet, the plethora of sources for endoscopic images, such as different processor-endoscope combinations or capsule endoscopy devices...

A monocular endoscopic image depth estimation method based on a window-adaptive asymmetric dual-branch Siamese network.

Scientific reports
Minimally invasive surgery involves entering the body through small incisions or natural orifices, using a medical endoscope for observation and clinical procedures. However, traditional endoscopic images often suffer from low texture and uneven illu...

Improving Foundation Model for Endoscopy Video Analysis via Representation Learning on Long Sequences.

IEEE journal of biomedical and health informatics
Recent advancements in endoscopy video analysis have relied on the utilization of relatively short video clips extracted from longer videos or millions of individual frames. However, these approaches tend to neglect the domain-specific characteristic...