Paolo Fiorini

University of Verona | UNIVR · Department of Computer Science

The IEEE Transactions on Medical Robotics and Bionics (T-MRB) is an initiative shared by the two IEEE Societies of Robotics and Automation – RAS – and Engineering in Medicine and Biology – EMBS.

A Chronic Total Occlusion (CTO) is a type of arte- rial blockage, which has persisted for more than three months, affecting the coronary arteries of the heart. Traditionally, CTO is treated by making a large incision in the chest area. This is a highly invasive procedure. Instead, catheter based approaches offer smaller inci- sions and exploit the...

Automation holds the potential to assist surgeons in robotic interventions, shifting their mental work load from visuomotor control to high level decision making. Reinforcement learning has shown promising results in learning complex visuomotor policies, especially in simulation environments where many samples can be collected at low cost. A core c...

Cable-driven mechanism models are, usually, included in actuated systems; however, recently, their use for sensitive systems has been explored. In this paper, two cable-driven multi-body mechanism models are compared, underlining advantages and constraints in using sensitive cable-driven mechanisms for minimally invasive robotic instruments. The pr...

Transperineal prostate biopsy is the most reliable technique for detecting prostate cancer, and robot-assisted needle insertion has the potential to improve the accuracy of this procedure. Modeling the interaction between a bevel-tip needle and the tissue, considering tissue heterogeneity, needle bending, and tissue/organ deformation and movement i...

This paper presents a planar cable-driven model of a simple mechanism that is able to measure forces and displacements. Recently, a preliminary study based on a cable-driven sensitive mechanism was presented to the research community, underlining the innovative characteristics of the model in under-actuation and under-sensing. The core of the resea...

This study aims to evaluate the abdominal aortic atherosclerotic plaque index (API)’s predictive role in patients with pre-operatively or post-operatively developed chronic kidney disease (CKD) treated with robot-assisted partial nephrectomy (RAPN) for renal cell carcinoma (RCC). One hundred and eighty-three patients (134 with no pre- and post-oper...

While executing a surgical procedure, surgeons not only rely on their specific medical knowledge but also on a set of skills that are “obvious” to them and allow for intuitively evaluating and reacting to the intervention evolution. Such skills belong to what is usually called common sense , which is essential to carry out an intervention. Althou...

Natural language annotations and manuals can provide useful procedural information and relations for the highly specialized scenario of autonomous robotic task planning. In this paper, we propose and publicly release AUTOMATE, a pipeline for automatic task knowledge extraction from expert-written domain texts. AUTOMATE integrates semantic sentence...

Pre-trained language models are now ubiquitous in natural language processing, being successfully applied for many different tasks and in several real-world applications. However, even though there is a wealth of high-quality written materials on surgery, and the scientific community has shown a growing interest in the application of natural langua...

The Ieee Transactions on Medical Robotics and Bionics (T-MRB) is an initiative shared by the two IEEE Societies of Robotics and Automation – RAS – and Engineering in Medicine and Biology – EMBS.

Increased demand for less invasive procedures has accelerated the adoption of Intraluminal Procedures (IP) and Endovascular Interventions (EI) performed through body lumens and vessels. As navigation through lumens and vessels is quite complex, interest grows to establish autonomous navigation techniques for IP and EI for reaching the target area....

Research has demonstrated that Taekwondo training helps to enhance the coordination capabilities in people with developmental coordination disorders. These excellent results depend on many factors, including the behavior of the muscular activation patterns of psychomotor exercises during Taekwondo training. Our basic idea is to study the behavior o...

Objective During nerve-sparing robot-assisted radical prostatectomy (RARP) bipolar electrocoagulation is often used but its use is controversial for the possible thermal damage of neurovascular bundles. Aim of the study was to evaluate the spatial-temporal thermal distribution in the tissue and the correlation with the electrosurgery-induced tissue...

Force–torque sensors are used in many and different domains (i.e., space, medicine, biology, etc.). Design solutions of force–torque sensors can be conceived by using many types of connections or components; however, there are only a few sensors designed using cable-driven systems. This could be related to many reasons, one of which being that cabl...

Increased demand for less invasive procedures has accelerated the adoption of Intraluminal Procedures (IP) and Endovascular Interventions (EI) performed through body lumens and vessels. As navigation through lumens and vessels is quite complex, interest grows to establish autonomous navigation techniques for IP and EI for reaching the target area....

Automatic recognition of fine-grained surgical activities, called steps, is a challenging but crucial task for intelligent intra-operative computer assistance. The development of current vision-based activity recognition methods relies heavily on a high volume of manually annotated data. This data is difficult and time-consuming to generate and req...

Robot-assisted surgery is a multidisciplinary research field, which includes many subjects (e.g., medicine and surgery, engineering, mechanics, electronics, computer science, physics, chemical, material science, robotics and many others). Sensors for physical interaction, during robot-assisted surgery, integrate some of these disciplines and are an...

Purpose: Automatic recognition of surgical activities from intraoperative surgical videos is crucial for developing intelligent support systems for computer-assisted interventions. Current state-of-the-art recognition methods are based on deep learning where data augmentation has shown the potential to improve the generalization of these methods....

Image-guided biopsy is the most common technique for breast cancer diagnosis. Although magnetic resonance imaging (MRI) has the highest sensitivity in breast lesion detection, ultrasound (US) biopsy guidance is generally preferred due to its non-invasiveness and real-time image feedback during the insertion. In this work, we propose an autonomous r...

Latent variable models are widely used to perform unsupervised segmentation of time series in different context such as robotics, speech recognition, and economics. One of the most widely used latent variable model is the Auto-Regressive Hidden Markov Model (ARHMM), which combines a latent mode governed by a Markov chain dynamics with a linear Auto...

Automatic recognition of fine-grained surgical activities, called steps, is a challenging but crucial task for intelligent intra-operative computer assistance. The development of current vision-based activity recognition methods relies heavily on a high volume of manually annotated data. This data is difficult and time-consuming to generate and req...

Over the last decade, the use of robots in production and daily life has increased. With increasingly complex tasks and interaction in different environments including humans , robots are required a higher level of autonomy for efficient deliberation. Task planning is a key element of deliberation. It combines elementary operations into a structure...

Over the last decade, the use of robots in production and daily life has increased. With increasingly complex tasks and interaction in different environments including humans, robots are required a higher level of autonomy for efficient deliberation. Task planning is a key element of deliberation. It combines elementary operations into a structured...

The automatic extraction of procedural surgical knowledge from surgery manuals, academic papers or other high-quality textual resources, is of the utmost importance to develop knowledge-based clinical decision support systems, to automatically execute some procedure’s step or to summarize the procedural information, spread throughout the texts, in...

Flexible endoscopes for colonoscopy present several limitations due to their inherent complexity, resulting in patient discomfort and lack of intuitiveness for clinicians. Robotic devices together with autonomous control represent a viable solution to reduce the workload of endoscopists and the training time while improving the overall procedure ou...

Colonoscopy is the gold standard examination procedure for screening colorectal cancer (CRC), providing the ability to inspect the lower digestive tract [1]. Standard colonoscopy is carried out with a minimally invasive approach based on a flexible endoscope controlled by the steering knobs. However, for routine screening, the intrusive nature of t...

Prostate biopsy fusion systems employ manual segmentation of the prostate before the procedure, therefore the image registration is static. To pave the way for dynamic fusion, we introduce PROST-Net, a deep learning (DL) based method to segment the prostate in real-time. The algorithm works in three steps: firstly, it detects the presence of the pr...

Prostate biopsy is a manual procedure carried out mostly under ultrasound (US) guidance to confirm the presence of cancer. The standard biopsy is random and includes at least 12 insertions; targeted biopsy makes use of dedicated hardware and software, but is still performed manually. We present here the pre-clinical validation of PROST, a robot pri...

Advanced Sensing Technologies (ASTs) have a great potential to improve surgical quality and to further develop Surgical Robotic Systems (SRSs), enhancing their technical and autonomy capabilities. Among these sensing techniques, Electrical Bioimpedance (EBI) provides a non-invasive, low-cost, and safe AST for the intraoperative localization of abno...

Intraoperative tissue identification is important and frequently required in modern surgical approaches for guiding operation. For this purpose, a novel robot assisted sensing system equipping with a wide-band impedance spectroscope is developed. Without introducing an external sensor probe to the operating site, the proposed system incorporates tw...

Autonomous robotic surgery requires deliberation, i.e. the ability to plan and execute a task adapting to uncertain and dynamic environments. Uncertainty in the surgical domain is mainly related to the partial pre-operative knowledge about patient-specific anatomical properties. In this paper, we introduce a logic-based framework for surgical tasks...

The implementation of a thermal endoscope based on the LWIR camera cores Lepton and a custom miniaturized electronics is reported. The sensor and the PCB can be inserted into a cylindrical protective case of diameter down to 15mm, inox tube or plastic, 3D printable envelope, with an optical window in Germanium. Two PCBs were developed for assemblin...

Optical Coherence Tomography (OCT) is increasingly used in endoluminal procedures since it provides high-speed and high resolution imaging. Distortion and instability of images obtained with a proximal scanning endoscopic OCT system are significant due to the motor rotation irregularity, the friction between the rotating probe and outer sheath and...

Force control is nowadays a mature technology, widespread in modern robotics systems and commercialized within several application domains. However, assessing the performance of a force-controlled system is not a trivial task because it may be strongly influenced by the environment dynamics. Exerting a force on a soft environment is different from...

Automation holds the potential to assist surgeons in robotic interventions, shifting their mental work load from visuomotor control to high level decision making. Reinforcement learning has shown promising results in learning complex visuomotor policies, especially in simulation environments where many samples can be collected at low cost. A core c...

Optical Coherence Tomography (OCT) is an emerging medical imaging modality for luminal organ diagnosis. The non-constant rotation speed of optical components in the OCT catheter tip causes rotational distortion in OCT volumetric scanning. By improving the scanning process, this instability can be partially reduced. To further correct the rotational...

The electrical impedance tomography (EIT) technology is an important medical imaging approach to show the electrical characteristics and the homogeneity of a tissue region noninvasively. Recently, this technology has been introduced to the Robot Assisted Minimally Invasive Surgery (RAMIS) for assisting the detection of surgical margin with relevant...

Fiber-coupled laser tools combine the precision of lasers with the flexibility of optical fibers. They have been used in surgical procedures, such as transoral microsurgery, to perform precise incisions in delicate structures that are often difficult to reach with other tools. Unfortunately, the performance of fiber tools is not akin to that of tra...

Intra-operative local 3D vessel representations have the potential to significantly decrease the use of contrast agents and exposure to ionizing radiation during endovascular procedures, while overcoming the 2D visualization limitation of fluoroscopic guidance. By fusing intravascular ultrasound (IVUS) imaging and electromagnetic (EM) pose sensing...

Robot-assisted surgery is an established clinical practice. The automatic identification of surgical actions is needed for a range of applications, including performance assessment of trainees and surgical process modeling for autonomous execution and monitoring. However, supervised action identification is not feasible, due to the burden of manual...

The current research focus in Robot-Assisted Minimally Invasive Surgery (RAMIS) is directed towards increasing the level of robot autonomy, to place surgeons in a supervisory position. Although Learning from Demonstrations (LfD) approaches are among the preferred ways for an autonomous surgical system to learn expert gestures, they require a high n...

Patient-specific Biomechanical Models (PBMs) can enhance computer assisted surgical procedures with critical information. Although pre-operative data allow to parametrize such PBMs based on each patient’s properties, they are not able to fully characterize them. In particular, simulation boundary conditions cannot be determined from pre-operative m...

Deep Reinforcement Learning (DRL) is a viable solution for automating repetitive surgical subtasks due to its ability to learn complex behaviours in a dynamic environment. This task automation could lead to reduced surgeon's cognitive workload, increased precision in critical aspects of the surgery, and fewer patient-related complications. However,...

In this paper we propose a new methodology to model surgical procedures that is specifically tailored to semi-autonomous robotic surgery. We propose to use a restricted version of statecharts to merge the bottom-up approach, based on data-driven techniques (e.g. machine learning), with the top-down approach based on knowledge representation techniq...

When applied to industrial processes, predictive models (PMs) easily fail to depict the overall complexity of a production plant. Multiple factors can interfere during the production process and the requirements in accuracy, safety and efficiency are very high. To fully achieve the potential of PMs, it is useful to integrate typical characteristics...

The quality of robot-assisted surgery can be improved and the use of hospital resources can be optimized by enhancing autonomy and reliability in the robot’s operation. Logic programming is a good choice for task planning in robot-assisted surgery because it supports reliable reasoning with domain knowledge and increases transparency in the decisio...

Purpose We present the validation of PROST, a robotic device for prostate biopsy. PROST is designed to minimize human error by introducing some autonomy in the execution of the key steps of the procedure, i.e., target selection, image fusion and needle positioning. The robot allows executing a targeted biopsy through ultrasound (US) guidance and fu...

Dynamic Movement Primitives (DMPs) is a framework for learning a point-to-point trajectory from a demonstration. Despite being widely used, DMPs still present some shortcomings that may limit their usage in real robotic applications. Firstly, at the state of the art, mainly Gaussian basis functions have been used to perform function approximation....

In Robot Assisted Minimally Invasive Surgery, discriminating critical subsurface structures is essential to make the surgical procedure safer and more efficient. In this paper, a novel robot assisted electrical bio-impedance scanning (RAEIS) system is developed and validated using a series of experiments. The proposed system constructs a tri-polar...

Robot-assisted surgery is an established clinical practice. The automatic identification of surgical actions is needed for a range of applications, including performance assessment of trainees and surgical process modeling for autonomous execution and monitoring. However, supervised action identification is not feasible, due to the burden of manual...

Purpose Automatic segmentation and classification of surgical activity is crucial for providing advanced support in computer-assisted interventions and autonomous functionalities in robot-assisted surgeries. Prior works have focused on recognizing either coarse activities, such as phases, or fine-grained activities, such as gestures. This work aims...