Guang-Zhong Yang

South-Central University For Nationalities · pharmacy of college

Analog computing using non-volatile memristors has emerged as a promising solution for energy-efficient deep learning. New materials, like perovskites-based memristors are recently attractive due to their cost-effectiveness, energy efficiency and flexibility. Yet, challenges in material diversity and immature fabrications require extensive experime...

Purposes To enhance the functional capability of MRI, this study aims to develop a novel MR elastography (MRE) sequence that achieves rapid acquisition without distortion artifacts. Methods A displacement‐encoded stimulated echo (DENSE) with multiphase acquisition scheme was used to capture wave images. A center‐out golden‐angle stack‐of‐stars sam...

Cardiovascular diseases (CVDs), including congenital heart diseases (CHD), present significant global health challenges, emphasizing the need for safe and effective treatment modalities. Fluoroscopy‐guided endovascular interventions are widely utilized but raise concerns about ionizing radiation, especially in pediatric cases. Magnetic resonance im...

Domain adaptation, which bridges the distributions across different modalities, plays a crucial role in multimodal medical image analysis. In endoscopic imaging, combining pre-operative data with intra-operative imaging is important for surgical planning and navigation. However, existing domain adaptation methods are hampered by distribution shift...

The implantation of multichannel, miniaturized, flexible neuroelectrodes for high-quality brain signal acquisition is of great importance for brain science research and brain–computer interfacing (BCI). However, slender and thin flexible neuroelectrodes usually require a tungsten probe as the shuttle to assist in penetrating the pia mater for impla...

Accurate assessment of lymph node size in 3D CT scans is crucial for cancer staging, therapeutic management, and monitoring treatment response. Existing state-of-the-art segmentation frameworks in medical imaging often rely on fully annotated datasets. However, for lymph node segmentation, these datasets are typically small due to the extensive tim...

Piperine, a natural amide isolated from the genus of Piper, serves as a pharmacophore in medicinal chemistry. In this study, we synthesised and evaluated 18 novel piperine-acylhydrazone hybrids (4a-4r) for their antiproliferative activities in vitro. The structures of these hybrids were validated using 1H,13C NMR, and HR-ESI-MS data. Furthermore, w...

Photoacoustic microscopy (PAM) has gained increasing popularity in biomedical imaging, providing new opportunities for tissue monitoring and characterization. With the development of deep learning techniques, convolutional neural networks have been used for PAM image resolution enhancement and denoising. However, there exist several inherent challe...

Magnetic resonance elastography (MRE) of brain relies on inducing and measuring shear waves in the brain. However, studies have shown vibration could induce changes in cerebral blood flow (CBF), which has a modulation effect and can affect the biomechanical properties measured. Objective: This work demonstrates the initial prototype of the indirect...

Cardiovascular diseases (CVDs) and congenital heart diseases (CHD) pose significant global health challenges. Fluoroscopy-guided endovascular interventions, though effective, are accompanied by ionizing radiation concerns, especially in pediatric cases. Magnetic resonance imaging (MRI) emerges as a radiation-free alternative, offering superior soft...

Background Different MR elastography (MRE) systems may produce different stiffness measurements, making direct comparison difficult in multi‐center investigations. Purpose To assess the repeatability and reproducibility of liver stiffness measured by three typical MRE systems. Study Type Prospective. Population/Phantoms Thirty volunteers without...

Robots are becoming ubiquitous in healthcare in recent years [1, 2]. To address the increasing demand in clinical applications, we have witnessed the popularity of medical robotics in surgery, rehabilitation, and personal assistance [2–8]. Another important category in medical robotics lies in the development of robotic systems to improve the autom...

This chapter presents an overview of the clinical aspects that influence the design, development, and uptake of surgical robots. It mainly focuses on the evolution of surgery and related clinical technologies, reporting clinical applications of robotic surgery, and analyzing clinical needs and challenges that are relevant to the translation and usa...

With an increasingly aged population all over the world and the prevalence of neurological and musculoskeletal disorders, the demand for rehabilitation and assistive devices is increasing. This chapter will provide a brief insight into the motivation for the development of rehabilitation and assistive robots. This chapter also emphasizes the clinic...

As introduced in Chap. 4, there exist diverse social factors and significant clinical demands that drive the development of rehabilitation and assistive robots. This chapter aims to provide an overview of the technical aspects of rehabilitation and assistive robotics. We will consider in sequence robots for therapeutic training, personal assistance...

The prosperity of robotics, mechanical engineering, material science, artificial intelligence, and biomedical engineering has an increasing impact on the conventional medical industry [1–3]. With the close integration of medicine and engineering, medical robotics has emerged for automated diagnosis, treatment, rehabilitation, and disease management...

This chapter provides an overview of the evolution of robotic surgery over the years, as well as the efforts undertaken in the integration of imaging, sensing, and robotics for improved human–robot interaction. It analyzes robotic platforms and technologies that have contributed to making robotic surgery a major area of innovation and development....

Precise manipulation of flexible surgical tools is crucial in minimally invasive surgical procedures, necessitating a miniature and flexible robotic probe that can precisely direct the surgical instruments. In this work, we developed a polymer-based robotic fiber with a thermal actuation mechanism by local heating along the sides of a single fiber....

One previously undescribed naphthoquinone-benzisochromanquinone dimer berpolydiquinone A (1), along with two previously undescribed naphthoquinone-anthraquinone dimers berpolydiquinones B and C (2-3), and one previously undescribed dimeric naphthalene berpolydinaphthalene A (4), were isolated from the stems and leaves of Berchemia polyphylla var. l...

Cable-driven continuum robots are widely used for endoluminal intervention because of their dexterity and shape conforming steerability. However, body contact between the continuum robot and its surrounding anatomy is unavoidable, which imposes a potential safety risk, including vessel wall damage or even perforation. This paper presents an approac...

Three new anthraquinone-benzisochromanquinone dimers polyphylldiquinones A-C (1-3), along with three known analogs floribundiquinone A-B (4-5) and 7-dehydroxyventiloquinone H (6), were isolated from the stems and leaves of Berchemia polyphylla. The chemical structures and absolute configurations of these compounds were determined using HR-ESI-MS, s...

Accurate navigation and targeting are critical for neurological interventions including biopsy and deep brain stimulation. Real-time image guidance further improves surgical planning and MRI is ideally suited for both pre- and intra-operative imaging. However, balancing spatial and temporal resolution is a major challenge for real-time intervention...

MotorImagery(MI) Electroencephalography(EEG) is one of the most common Brain-Computer Interface (BCI) paradigms that has been widely used in neural rehabilitation and gaming. Although considerable research efforts have been dedicated to developing MI EEG classification algorithms, they are mostly limited in handling scenarios where the training and...

Progressive stenosis of blood vessels is an important cause of cardiovascular diseases. Traditional intervention methods rely on fluoroscopy, which exposes both patients and operators to ionizing radiation. In this article, we propose a real-time detection method for vascular stenosis intervention based on fiber Bragg grating (FBG) sensors that can...

Robotic telemedicine can provide timely treatment to critical patients in geographically remote locations. However, owing to the lack of depth information, occlusion of instrument, and view direction limitations, visual feedback from the patient to the clinician is typically unintuitive, which affects surgical safety. Herein, an omnidirectional aug...

The integration of machine/deep learning and sensing technologies is transforming healthcare and medical practice. However, inherent limitations in healthcare data, namely scarcity , quality , and heterogeneity , hinder the effectiveness of supervised learning techniques which are mainly based on pure statistical fitting between data and labe...

p>Photoacoustic microscopy (PAM) has gained increasing popularity in biomedical imaging, providing new opportunities for tissue monitoring and characterization. Resolution enhancement and denoising are two critical tasks for PAM image reconstruction and post-processing. With the development of deep learning techniques, Convolutional Neural Networks...

Magnetic Resonance Imaging (MRI) is now a widely used modality for providing multimodal, high-quality soft tissue contrast images with good spatiotemporal resolution but without subjecting patients to ionizing radiation. In addition to its diagnostic potential, its future theranostic value lies in its ability to provide MRI-guided robot interventio...

p>Photoacoustic microscopy (PAM) has gained increasing popularity in biomedical imaging, providing new opportunities for tissue monitoring and characterization. Resolution enhancement and denoising are two critical tasks for PAM image reconstruction and post-processing. With the development of deep learning techniques, Convolutional Neural Networks...

p>Photoacoustic microscopy (PAM) has gained increasing popularity in biomedical imaging, providing new opportunities for tissue monitoring and characterization. Resolution enhancement and denoising are two critical tasks for PAM image reconstruction and post-processing. With the development of deep learning techniques, Convolutional Neural Networks...

https://youtu.be/FdyuhoHNoqU Master-Slave control is a common mode of operation for surgical robots as it ensures that surgeons are always in control and responsible for the procedure. Most teleoperated surgical systems use low degree-of-freedom (DOF) instruments, thus facilitating direct mapping of manipulator position to the instrument pose and t...

PurposeEndobronchial intervention requires detailed modeling of pulmonary anatomical substructure, such as lung airway and artery-vein maps, which are commonly extracted from non-contrast computed tomography (NCCT) independently using automatic segmentation approaches. We aim to make the first attempt to jointly train a CNN-based model for airway a...

Endomicroscopy is an emerging imaging modality for real-time optical biopsy. One limitation of existing endomicroscopy based on coherent fibre bundles is that the image resolution is intrinsically limited by the number of fibres that can be practically integrated within the small imaging probe. To improve the image resolution, Super-Resolution (SR)...

Analog deep neural networks (DNNs) provide a promising solution, especially for deployment on resource-limited platforms, for example in mobile settings. However, the practicability of analog DNNs has been limited by their instability due to multi-factor reasons from manufacturing, thermal noise, etc. Here, we present a theoretically guaranteed noi...

Endobronchial intervention is increasingly used as a minimally invasive means for the treatment of pulmonary diseases. In order to reduce the difficulty of manipulation in complex airway networks, robust lumen detection is essential for intraoperative guidance. However, these methods are sensitive to visual artifacts which are inevitable during the...

Open international challenges are becoming the de facto standard for assessing computer vision and image analysis algorithms. In recent years, new methods have extended the reach of pulmonary airway segmentation that is closer to the limit of image resolution. Since EXACT'09 pulmonary airway segmentation, limited effort has been directed to quantit...

Microactuators can autonomously convert external energy into specific mechanical motions. With the feature sizes varying from the micrometer to millimeter scale, microactuators offer many operation and control possibilities for miniaturized devices. In recent years, advanced microfluidic techniques have revolutionized the fabrication, actuation, an...

Technologies that rely on the fundamental principle of thermal expansion have demonstrated high-precision, a growing demand in fields driven by miniaturization. However, scalable production of high aspect ratio devices that harness this capability while facilitating flexibility in design and functionality remains a challenge. We employed the high-t...

Fabrication of actuatable micromechanisms onto the tip of submillimeter medical instruments permits microsurgery, cellular‐level intervention, targeted drug delivery, or placement of microimplants. In these systems, a common lack of integrated microsensors or optical feedback prohibits stabilizing closed‐loop control. Moreover, the low stiffness of...

Egocentric vision has gained increasing popularity recently, opening new avenues for human-centric applications. However, the use of the egocentric fisheye cameras allows wide angle coverage but image distortion is introduced along with strong human body self-occlusion imposing significant challenges in data processing and model reconstruction. Unl...

italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Objective: In-vivo validation on animal setting of a pneumatically propelled robot for endovascular intervention, to determine safety and clinical advantage of robotic cannulations compared to manual operation. Methods: Robotic assistance and image-g...

With the use of tendon-driven continuum manipulators, it is possible to reach deep-seated small lesions in a constrained anatomical space. This circumvents the difficulties encountered by existing straight endoscopes and surgical instruments, which require direct line of sight access during inspection and operation. However, maintaining adequate st...

Robotic telemedicine has a high potential to promote the development of future medicine. It enables the treatment of critical patients in geographically remote locations in time, and also particularly useful for avoiding infection risks during pandemics of infectious diseases. However, visual feedback from the patient’s side to the clinician’s side...

Accurate nodule labeling and interpretable machine learning are important for lung cancer diagnosis. To circumvent the label ambiguity issue of commonly-used unsure nodule data such as LIDC-IDRI, we constructed a sure nodule data with gold-standard clinical diagnosis. To make the traditional CNN networks interpretable, we propose herewith a novel c...

The success of most advanced facial expression recognition works relies heavily on large-scale annotated datasets. However, it poses great challenges in acquiring clean and consistent annotations for facial expression datasets. On the other hand, self-supervised contrastive learning has gained great popularity due to its simple yet effective instan...

Optical manipulation is a technology that enables accurate manipulation of micro-robots in fluidic environment. Optical micro-robots, which can be used as micro-tools to perform indirect micro-objects manipulation via optical tweezers (OT), have been employed for various biomedical applications. Supported by the latest advances in three-dimensional...

Detailed pulmonary airway segmentation is a clinically important task for endobronchial intervention and treatment of peripheral lung cancer lesions. Convolutional Neural Networks (CNNs) are promising tools for medical image analysis but have been performing poorly for cases when there is a significantly imbalanced feature distribution, which is tr...

Detailed modeling of the airway tree from CT scan is important for 3D navigation involved in endobronchial intervention including for those patients infected with the novel coronavirus. Deep learning methods have the potential for automatic airway segmentation but require large annotated datasets for training, which is difficult for a small patient...

The LIDC-IDRI database is the most popular benchmark for lung cancer prediction. However, with subjective assessment from radiologists, nodules in LIDC may have entirely different malignancy annotations from the pathological ground truth, introducing label assignment errors and subsequent supervision bias during training. The LIDC database thus req...

Detailed anatomical labeling of bronchial trees extracted from CT images can be used as fine-grained maps for intra-operative navigation. To cater to the sparse distribution of airway voxels and large class imbalance in 3D image space, a graph-neural-network-based method is proposed to map branches to nodes in a graph space and assign anatomical la...

Recent evolution in deep learning has proven its value for CT-based lung nodule classification. Most current techniques are intrinsically black-box systems, suffering from two generalizability issues in clinical practice. First, benign-malignant discrimination is often assessed by human observers without pathologic diagnoses at the nodule level. We...

Accurate motion and depth recovery is important for many robot vision tasks including autonomous driving. Most previous studies have achieved cooperative multi-task interaction via either pre-defined loss functions or cross-domain prediction. This paper presents a multi-task scheme that achieves mutual assistance by means of our Flow to Depth (F2D)...

Objective: The technique of robust suture detection is vital in many applications including the skill evaluation for trainee, and suture augmentation in robotic-assisted surgery. Due to the complicated environment in surgery, the pose estimation of suture threads is challenged by the foreground and the background occlusion. Methods: To address t...

Neurological disorders represent one of the leading causes of disability and mortality in the world. Parkinson's Disease (PD), for example, affecting millions of people worldwide is often manifested as impaired posture and gait. These impairments have been used as a clinical sign for the early detection of PD, as well as an objective index for perv...

The LIDC-IDRI database is the most popular benchmark for lung cancer prediction. However, with subjective assessment from radiologists, nodules in LIDC may have entirely different malignancy annotations from the pathological ground truth, introducing label assignment errors and subsequent supervision bias during training. The LIDC database thus req...

Endobronchial intervention is increasingly used as a minimally invasive means for the treatment of pulmonary diseases. In order to acquire the position of bronchoscopy, vision-based localization approaches are clinically preferable but are sensitive to visual variations. The static nature of pre-operative planning makes mapping of intraoperative an...

Representation learning is the critical task for medical image analysis in computer-aided diagnosis. However, it is challenging to learn discriminative features due to the limited size of the dataset and the lack of labels. In this paper, we propose a stochastic routing normalization and neighborhood embedding framework with application to breast t...

Medical robotics is a rapidly advancing discipline that is leading the evolution of robot-assisted surgery, personalized rehabilitation and assistance, and hospital automation. In China, both research and commercial developments in medical robotics have undergone exponential growth in recent years. In this review, we first give an overview of the c...

Totally implanted access ports (TIAP) are widely used with oncology patients requiring long term central venous access for the delivery of chemotherapeutic agents, infusions, transfusions, blood sample collection and parenteral nutrition. Such devices offer a significant improvement to the quality of life for patients and reduced complication rates...

Human-robot shared control, which integrates the advantages of both humans and robots, is an effective approach to facilitate efficient surgical operation. Learning from demonstration (LfD) techniques can be used to automate some of the surgical subtasks for the construction of the shared control mechanism. However, a sufficient amount of data is r...

Three-dimensional (3D) pose estimation of micro/nano-objects is essential for the implementation of automatic manipulation in micro/nano-robotic systems. However, out-of-plane pose estimation of a micro/nano-object is challenging, since the images are typically obtained in 2D using a scanning electron microscope (SEM) or an optical microscope (OM)....

Purpose: With the increasing usage of stereo cameras in computer-assisted surgery techniques, surgeons can benefit from better 3D context of the surgical site in minimally invasive operations. However, since stereo cameras are placed together at the confined endoscope tip, the size of lens and sensors is limited, resulting in low resolution of ste...