A multiple catheter tips tracking method in X-ray fluoroscopy images by a new lightweight segmentation network and Bayesian filtering.

During percutaneous coronary intervention, the guiding catheter plays an important role. Tracking the catheter tip placed at the coronary ostium in the X-ray fluoroscopy sequence can obtain image displacement information caused by the heart beating, which can help dynamic coronary roadmap overlap on X-ray fluoroscopy images. Due to a low exposure dose, the X-ray fluoroscopy is noisy and low contrast, which causes some difficulties in tracking.

Automatic segmentation for plan-of-the-day selection in CBCT-guided adaptive radiation therapy of cervical cancer.

Plan-of-the-day (PoD) adaptive radiation therapy (ART) is based on a library of treatment plans, among which, at each treatment fraction, the PoD is selected using daily images. However, this strategy is limited by PoD selection uncertainties. This work aimed to propose and evaluate a workflow to automatically and quantitatively identify the PoD for cervix cancer ART based on daily CBCT images.

Measurement and Analysis of Lobar Lung Deformation After a Change of Patient Position During Video-Assisted Thoracoscopic Surgery.

Video-assisted thoracoscopic surgery (VATS) is a minimally invasive surgical technique for the diagnosis and treatment of early-stage lung cancer. During VATS, large lung deformation occurs as a result of a change of patient position and a pneumothorax (lung deflation), which hinders the intraoperative localization of pulmonary nodules. Modeling lung deformation during VATS for surgical navigation is desirable, but the mechanisms causing such deformation are yet not well-understood.

Interest of the minimum edit distance to detect behaviour change of the elderly person.

In this article, a solution to detect the change of behaviour of the elderly person based on the person's activities of daily living is proposed. This work is based on the hypothesis that the person attaches importance to a rhythmic sequence of days and activities per day. The day of the elderly person is described by a succession of activities, and each activity is associated to a posture (lying down, sitting, standing, absent).

Meta grayscale adaptive network for 3D integrated renal structures segmentation.

Three-dimensional (3D) integrated renal structures (IRS) segmentation targets segmenting the kidneys, renal tumors, arteries, and veins in one inference. Clinicians will benefit from the 3D IRS visual model for accurate preoperative planning and intraoperative guidance of laparoscopic partial nephrectomy (LPN). However, no success has been reported in 3D IRS segmentation due to the inherent challenges in grayscale distribution: low contrast caused by the narrow task-dependent distribution range of regions of interest (ROIs), and the networks representation preferences caused by the distribution variation inter-images.

A hybrid, image-based and biomechanics-based registration approach to markerless intraoperative nodule localization during video-assisted thoracoscopic surgery.

The resection of small, low-dense or deep lung nodules during video-assisted thoracoscopic surgery (VATS) is surgically challenging. Nodule localization methods in clinical practice typically rely on the preoperative placement of markers, which may lead to clinical complications. We propose a markerless lung nodule localization framework for VATS based on a hybrid method combining intraoperative cone-beam CT (CBCT) imaging, free-form deformation image registration, and a poroelastic lung model with allowance for air evacuation.

Deformable US/CT Image Registration with a Convolutional Neural Network for Cardiac Arrhythmia Therapy.

Image registration represents one of the fundamental techniques in medical imaging and image-guided interventions. In this paper, we present a Convolutional Neural Network (CNN) framework for deformable transesophageal US/CT image registration, for the cardiac arrhythmias, and guidance therapy purposes. The framework consists of a CNN, a spatial transformer, and a resampler.

Dense biased networks with deep priori anatomy and hard region adaptation: Semi-supervised learning for fine renal artery segmentation.

Fine renal artery segmentation on abdominal CT angiography (CTA) image is one of the most important tasks for kidney disease diagnosis and pre-operative planning. It will help clinicians locate each interlobar artery's blood-feeding region via providing the complete 3D renal artery tree masks. However, it is still a task of great challenges due to the large intra-scale changes, large inter-anatomy variation, thin structures, small volume ratio and small labeled dataset of the fine renal artery.

HIFUNet: Multi-Class Segmentation of Uterine Regions From MR Images Using Global Convolutional Networks for HIFU Surgery Planning.

Accurate segmentation of uterus, uterine fibroids, and spine from MR images is crucial for high intensity focused ultrasound (HIFU) therapy but remains still difficult to achieve because of 1) the large shape and size variations among individuals, 2) the low contrast between adjacent organs and tissues, and 3) the unknown number of uterine fibroids. To tackle this problem, in this paper, we propose a large kernel Encoder-Decoder Network based on a 2D segmentation model. The use of this large kernel can capture multi-scale contexts by enlarging the valid receptive field.

Weakly-supervised convolutional neural networks of renal tumor segmentation in abdominal CTA images.

Background: Renal cancer is one of the 10 most common cancers in human beings. The laparoscopic partial nephrectomy (LPN) is an effective way to treat renal cancer. Localization and delineation of the renal tumor from pre-operative CT Angiography (CTA) is an important step for LPN surgery planning.

Transrectal ultrasound image-based real-time augmented reality guidance in robot-assisted laparoscopic rectal surgery: a proof-of-concept study.

Purpose: Surgical treatments for low-rectal cancer require careful considerations due to the low location of cancer in rectums. Successful surgical outcomes highly depend on surgeons' ability to determine clear distal margins of rectal tumors. This is a challenge for surgeons in robot-assisted laparoscopic surgery, since tumors are often concealed in rectums and robotic surgical instruments do not provide tactile feedback for tissue diagnosis in real time.

Fast and accurate segmentation method of active shape model with Rayleigh mixture model clustering for prostate ultrasound images.

Background And Objective: The prostate cancer interventions, which need an accurate prostate segmentation, are performed under ultrasound imaging guidance. However, prostate ultrasound segmentation is facing two challenges. The first is the low signal-to-noise ratio and inhomogeneity of the ultrasound image.

Fast And Simple Automatic 3D Ultrasound Probe Calibration Based On 3D Printed Phantom And An Untracked Marker.

Tracking the pose of an ultrasound (US) probe is essential for an intraoperative US-based navigation system. The tracking requires mounting a marker on the US probe and calibrating the probe. The goal of the US probe calibration is to determine the rigid transformation between the coordinate system (CS) of the image and the CS of the marker mounted on the probe.

Transesophageal 2D ultrasound to 3D computed tomography registration for the guidance of a cardiac arrhythmia therapy.

The work aims to develop a new image-processing method to improve the guidance of transesophageal high intensity focused ultrasound (HIFU) atrial fibrillation therapy. Our proposal is a novel registration approach that aligns intraoperative 2D ultrasound with preoperative 3D-CT information. This approach takes advantage of the anatomical constraints imposed at the transesophageal HIFU probe to simplify the registration process.

A new stationary gridline artifact suppression method based on the 2D discrete wavelet transform.

Purpose: In digital x-ray radiography, an antiscatter grid is inserted between the patient and the image receptor to reduce scattered radiation. If the antiscatter grid is used in a stationary way, gridline artifacts will appear in the final image. In most of the gridline removal image processing methods, the useful information with spatial frequencies close to that of the gridline is usually lost or degraded.

Benchmark for Algorithms Segmenting the Left Atrium From 3D CT and MRI Datasets.

Knowledge of left atrial (LA) anatomy is important for atrial fibrillation ablation guidance, fibrosis quantification and biophysical modelling. Segmentation of the LA from Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) images is a complex problem. This manuscript presents a benchmark to evaluate algorithms that address LA segmentation.

Adaptation and evaluation of the multiple organs OSD for T2 MRI prostate segmentation.

This paper deals with the adaptation, the tuning and the evaluation of the multiple organs Optimal Surface Detection (OSD) algorithm for the T2 MRI prostate segmentation. This algorithm is initialized by first surface approximations of the prostate (obtained after a model adjustment), the bladder (obtained automatically) and the rectum (interactive geometrical model). These three organs are then segmented together in a multiple organs OSD scheme which proposes a competition between the gray level characteristics and some topological and anatomical information of these three organs.

Region and boundary feature estimation on ultrasound images using moment invariants.

In ultrasound images, tissues are characterized by their speckle texture. Moment-based techniques have proven their ability to capture texture features. However, in ultrasound images, the speckle size increases with the distance from the probe and in some cases the speckle has a concentric texture arrangement.

Phase estimation for a phased array therapeutic interstitial ultrasound probe.

This paper deals about high intensity ultrasound interstitial therapy simulation. The simulated phased array ultrasound probe allows a dynamic electronic focusing of the therapeutic beam. In order to maximize the power deposit at the focal point we propose a method which allows to optimally defining the phase shift of the electrical control signal for each individual element.

Bladder segmentation in MRI images using active region growing model.

Prostate segmentation in MRI may be difficult at the interface with the bladder where the contrast is poor. Coupled-models that segment simultaneously both organs with non-overlapping constraints offer a good solution. As a pre-segmentation of the structures of interest is required, we propose in this paper a fast deformable model to segment the bladder.

[From medical imaging to image-guided therapy].

This survey on medical imaging provides a look into three major components. The first one deals with the full steps through which it must be apprehended: from the sensors to the reconstruction, from the image analysis up to its interpretation. The second aspect describes the physical principles used for imaging (magnetic resonance, acoustic, optics, etc.

Image-guided therapy: evolution and breakthrough.

Beyond the advances made in computer-assisted interventions and robotic systems, the demand for more efficient and safer therapies remains challenging. Thus, if it is possible to improve the instrument tracking, steering, and target localization, to miniaturize the sensors and actuators, and to conduct preoperatively planned minimally invasive therapies, we still need new resources to achieve permanent destruction of abnormal tissues or suppression of pathological processes. Most of the physics-based (or energy-based) therapeutic principles at our disposal have been established a long time ago, but their actions on basic cellular and molecular mechanisms are not yet fully understood.