Artificial intelligence and automation in endoscopy and surgery
Modern endoscopy relies on digital technology, from high-resolution imaging sensors and
displays to electronics connecting configurable illumination and actuation systems for …
displays to electronics connecting configurable illumination and actuation systems for …
Frontiers of robotic colonoscopy: A comprehensive review of robotic colonoscopes and technologies
Flexible colonoscopy remains the prime mean of screening for colorectal cancer (CRC) and
the gold standard of all population-based screening pathways around the world. Almost …
the gold standard of all population-based screening pathways around the world. Almost …
Medical image analysis based on deep learning approach
Medical imaging plays a significant role in different clinical applications such as medical
procedures used for early detection, monitoring, diagnosis, and treatment evaluation of …
procedures used for early detection, monitoring, diagnosis, and treatment evaluation of …
Automatic instrument segmentation in robot-assisted surgery using deep learning
Semantic segmentation of robotic instruments is an important problem for the robot-assisted
surgery. One of the main challenges is to correctly detect an instrument's position for the …
surgery. One of the main challenges is to correctly detect an instrument's position for the …
Computer-aided gastrointestinal diseases analysis from wireless capsule endoscopy: a framework of best features selection
The continuous improvements in the area of medical imaging, makes the patient monitoring
a crucial concern. The internet of things (IoT) embedded in a medical technologies to collect …
a crucial concern. The internet of things (IoT) embedded in a medical technologies to collect …
Classification of stomach infections: A paradigm of convolutional neural network along with classical features fusion and selection
Automated detection and classification of gastric infections (ie, ulcer, polyp, esophagitis, and
bleeding) through wireless capsule endoscopy (WCE) is still a key challenge. Doctors can …
bleeding) through wireless capsule endoscopy (WCE) is still a key challenge. Doctors can …
Content-based brain tumor retrieval for MR images using transfer learning
This paper presents an automatic content-based image retrieval (CBIR) system for brain
tumors on T1-weighted contrast-enhanced magnetic resonance images (CE-MRI). The key …
tumors on T1-weighted contrast-enhanced magnetic resonance images (CE-MRI). The key …
Cholecseg8k: a semantic segmentation dataset for laparoscopic cholecystectomy based on cholec80
WY Hong, CL Kao, YH Kuo, JR Wang… - arxiv preprint arxiv …, 2020 - arxiv.org
Computer-assisted surgery has been developed to enhance surgery correctness and safety.
However, researchers and engineers suffer from limited annotated data to develop and train …
However, researchers and engineers suffer from limited annotated data to develop and train …
Attention aware deep learning model for wireless capsule endoscopy lesion classification and localization
P Muruganantham, SM Balakrishnan - Journal of Medical and Biological …, 2022 - Springer
Purpose Wireless capsule endoscopy (WCE) is a fundamental diagnosing tool for gastro-
intestinal (GI) lesion detection. Detecting and locating the lesions in WCE images using a …
intestinal (GI) lesion detection. Detecting and locating the lesions in WCE images using a …
[HTML][HTML] DSRD-Net: Dual-stream residual dense network for semantic segmentation of instruments in robot-assisted surgery
T Mahmood, SW Cho, KR Park - Expert Systems with Applications, 2022 - Elsevier
In conventional robot-assisted minimally invasive procedures (RMIS), surgeons have narrow
visual and complex working spaces, along with specular reflection, blood, camera-lens …
visual and complex working spaces, along with specular reflection, blood, camera-lens …