Deep convolutional generative adversarial network for inverse kinematics of self-assembly robotic arm based on the depth sensor
In this study, we propose a new deep convolutional generative adversarial kinematics
network (DCGAKN) to establish inverse kinematics of self-assembly robotic arm. We design …
network (DCGAKN) to establish inverse kinematics of self-assembly robotic arm. We design …
[HTML][HTML] ArthroNet: a monocular depth estimation technique with 3D segmented maps for knee arthroscopy
Background Lack of depth perception from medical imaging systems is one of the long-
standing technological limitations of minimally invasive surgeries. The ability to visualize …
standing technological limitations of minimally invasive surgeries. The ability to visualize …
Computer Assisted and Virtual Reality Based Robotic Knee Arthroscopy: A Systematic Review
Knee arthroscopy (KA) is an outpatient procedure in high demand, with many finding it a
potential beneficiary of robotic minimally invasive surgery. This literature study focuses on …
potential beneficiary of robotic minimally invasive surgery. This literature study focuses on …
3D semantic mapping from arthroscopy using out-of-distribution pose and depth and in-distribution segmentation training
Minimally invasive surgery (MIS) has many documented advantages, but the surgeon's
limited visual contact with the scene can be problematic. Hence, systems that can help …
limited visual contact with the scene can be problematic. Hence, systems that can help …
One step surgical scene restoration for robot assisted minimally invasive surgery
Minimally invasive surgery (MIS) offers several advantages to patients including minimum
blood loss and quick recovery time. However, lack of tactile or haptic feedback and poor …
blood loss and quick recovery time. However, lack of tactile or haptic feedback and poor …
Towards robotic knee arthroscopy: spatial and spectral learning model for surgical scene segmentation
Minimally invasive surgeries are complex to perform, and surgical outcomes are varied due
to a limited view of the surgical scene. There is a lack of reliable vision systems that can …
to a limited view of the surgical scene. There is a lack of reliable vision systems that can …
Sugarcane diseases identification and detection via machine learning
M Mostafizur Rahman Komol, M Sabid Hasan… - Computer Vision and …, 2023 - Springer
Sugarcane diseases are major concern for the global sugarcane market, as they can
significantly impact crop yield and quality. This can result in economic losses for farmers and …
significantly impact crop yield and quality. This can result in economic losses for farmers and …
Arthroscopic scene segmentation using multispectral reconstructed frames and deep learning
Background Knee arthroscopy is one of the most complex minimally invasive surgeries, and
it is routinely performed to treat a range of ailments and injuries to the knee joint. Its complex …
it is routinely performed to treat a range of ailments and injuries to the knee joint. Its complex …
Surface reflectance: a metric for untextured surgical scene segmentation
Segmentation is a process to understand scene context captured by a camera, and it is
commonly used to solve many robotic problems such as localization and tracking. The utility …
commonly used to solve many robotic problems such as localization and tracking. The utility …
Towards robotic knee arthroscopy: multi-scale network for tissue-tool segmentation
Tissue awareness has a great demand to improve surgical accuracy in minimally invasive
procedures. In arthroscopy, it is one of the challenging tasks due to surgical sites exhibit …
procedures. In arthroscopy, it is one of the challenging tasks due to surgical sites exhibit …