Related papers: Predicting respiratory motion for real-time tumour…
Robotic-assisted orthopaedic surgeries demand accurate, automated leg manipulation for improved spatial accuracy to reduce iatrogenic damage. In this study, we propose novel rigid body designs and an optical tracking volume setup for…
We present a method for human pose tracking that is based on learning spatiotemporal relationships among joints. Beyond generating the heatmap of a joint in a given frame, our system also learns to predict the offset of the joint from a…
This report reviews recent advancements in human motion prediction, reconstruction, and generation. Human motion prediction focuses on forecasting future poses and movements from historical data, addressing challenges like nonlinear…
Intraoperative ultrasound facilitates localisation of tumour boundaries during minimally invasive procedures. Autonomous ultrasound scanning systems have been recently proposed to improve scanning accuracy and reduce surgeons' cognitive…
Radiotherapy planning is a critical aspect of cancer treatment, where the optimal selection of beam directions and dose distributions significantly impacts treatment efficacy and patient outcomes. Traditionally, this process involves…
Temporal alignment is an inherent task in most applications dealing with videos: action recognition, motion transfer, virtual trainers, rehabilitation, etc. In this paper we dive into the understanding of this task from a geometric point of…
Purpose: To develop a fully automatic method for extraction and directionality determination of respiratory signal in free-breathing, real-time (RT) cardiac MRI. Methods: The respiratory signal is extracted by a principal component analysis…
High-dose-rate brachytherapy is a tumor treatment method where a highly radioactive source is brought in close proximity to the tumor. In this paper we develop a simulated annealing algorithm to optimize the dwell times at preselected dwell…
Objectives: Pancreatic cancer is a lethal disease, hard to diagnose and usually results in poor prognosis and high mortality. Developing an artificial intelligence (AI) algorithm to accurately and universally predict the early cancer risk…
Precision in radiation therapy relies on immobilization systems that limit patient motion. Thermoplastic masks are commonly used for this purpose, but subtle voluntary and involuntary movements such as jaw shifts, deep breathing, or eye…
In the realm of medical science, the pursuit of enhancing treatment efficacy and patient outcomes continues to drive innovation. This study delves into the integration of biomimicry principles within the domain of Radiation Therapy (RT) to…
Glioma, an aggressive brain malignancy characterized by rapid progression and its poor prognosis, poses significant challenges for accurate evolution prediction. These challenges are exacerbated by sparse, irregularly acquired longitudinal…
Motion analysis is used in computer vision to understand the behaviour of moving objects in sequences of images. Optimising the interpretation of dynamic biological systems requires accurate and precise motion tracking as well as efficient…
This paper primarily addresses a dataset relating to cellular, chemical and physical conditions of patients gathered at the time they are operated upon to remove colorectal tumours. This data provides a unique insight into the biochemical…
Medical Resonance Imaging or MRI is a medical image processing technique that used radio waves to scan the body. It is a tomographic imaging technique, principally used in the field of radiology. With the advantage of being a painless…
In this paper, we propose a system to detect brain tumor in 3D MRI brain scans of Flair modality. It performs 2 functions: (a) predicting gray-level and locational distributions of the pixels in the tumor regions and (b) generating tumor…
To develop an automated workflow for rectal cancer three-dimensional conformal radiotherapy treatment planning that combines deep-learning(DL) aperture predictions and forward-planning algorithms. We designed an algorithm to automate the…
Near infrared diffuse optical tomography (DOT) provides an imaging modality for the oxygenation of tissue. In this paper, we propose a novel machine learning algorithm based on time-domain radiative transfer equation. We use temporal…
Brain tumor resection is a highly complex procedure with profound implications for survival and quality of life. Predicting patient outcomes is crucial to guide clinicians in balancing oncological control with preservation of neurological…
We address the problem of (a) predicting the trajectory of an arm reaching motion, based on a few seconds of the motion's onset, and (b) leveraging this predictor to facilitate shared-control manipulation tasks, easing the cognitive load of…