Search results for " Medical imaging"

Automatic multi-seed detection for MR breast image segmentation

2017

In this paper an automatic multi-seed detection method for magnetic resonance (MR) breast image segmentation is presented. The proposed method consists of three steps: (1) pre-processing step to locate three regions of interest (axillary and sternal regions); (2) processing step to detect maximum concavity points for each region of interest; (3) breast image segmentation step. Traditional manual segmentation methods require radiological expertise and they usually are very tiring and time-consuming. The approach is fast because the multi-seed detection is based on geometric properties of the ROI. When the maximum concavity points of the breast regions have been detected, region growing and m…

Proposition of Convolutional Neural Network Based System for Skin Cancer Detection

2019

Skin cancer automated diagnosis tools play a vital role in timely screening, helping dermatologists focus on melanoma cases. Best arts on automated melanoma screening use deep learning-based approaches, especially deep convolutional neural networks (CNN) to improve performances. Because of the large number of parameters that could be involved during training in CNN many training samples are needed to avoid overfitting problem. Gabor filtering can efficiently extract spatial information including edges and textures, which may reduce the features extraction burden to CNN. In this paper, we proposed a Gabor Convolutional Network (GCN) model to improve the performance of automated diagnosis of …

Graphical interface for designing geometries and processing DICOM images for PENELOPE

2016

One of he most difficult steps when preparing a Monte Carlo calculation is the design of their geometries. Such process is an error-prone, time-consuming, and complex step for any simulation in the field of medical physics. The software VoxelMages has been developed to help the user in this complex task. It allows to design arbitrary geometries and to process DICOM image files for simulations with the general-purpose Monte Carlo code PENELOPE. Its main characteristics are described in the following.

Hybrid 3D-ResNet Deep Learning Model for Automatic Segmentation of Thoracic Organs at Risk in CT Images

2020

In image radiation therapy, accurate segmentation of organs at risk (OARs) is a very essential task and has clinical applications in cancer treatment. The segmentation of organs close to lung, breast, or esophageal cancer is a routine and time-consuming process. The automatic segmentation of organs at risk would be an essential part of treatment planning for patients suffering radiotherapy. The position and shape variation, morphology inherent and low soft tissue contrast between neighboring organs across each patient’s scans is the challenging task for automatic segmentation of OARs in Computed Tomography (CT) images. The objective of this paper is to use automatic segmentation of the orga…

High performance of intravoxel incoherent motion diffusion MRI in detecting viral hepatitis-b induced liver fibrosis.

2019

Background: Recently a small cohort study demonstrated that intravoxel incoherent motion (IVIM) diffusion MRI can detect early stage liver fibrosis. Using modified IVIM data acquisition parameters, the current study aims to confirm this finding. Methods: Twenty-six healthy volunteers, three patients of chronic viral hepatitis-b but without fibrosis and one mild liver steatosis subject, and 12 viral hepatitis-b patients with fibrosis (stage 1–2=7, stage 3–4=5) were included in this study. With a 1.5-T MR scanner and respiration-gating, IVIM diffusion imaging was acquired using a single-shot echo-planar sequence with a b -value series of 2, 0, 1, 15, 20, 30, 45, 50, 60, 80, 100, 200, 300, 600…

A Rule-Based Method to Model Myocardial Fiber Orientation for Simulating Ventricular Outflow Tract Arrhythmias

2017

Comunicació presentada a: FIMH 2017 9th International Conference, celebrada a Toronto, Canadà, de l'11 al 13 de juny de 2017. Myocardial fiber orientation determines the propagation of electrical waves in the heart and the contraction of cardiac tissue. One common approach for assigning fiber orientation to cardiac anatomi- cal models are Rule-Based Methods (RBM). However, RBM have been developed to assimilate data mostly from the Left Ventricle. In conse- quence, fiber information from RBM does not match with histological data in other areas of the heart, having a negative impact in cardiac simulations beyond the LV. In this work, we present a RBM where fiber orientation is separately mode…

Re-exposure in cone beam CT of the dentomaxillofacial region: a retrospective study.

2018

Cone beam CT (CBCT) often uses a smaller field of view compared to conventional CT scans. This might lead to a wrong field of view with the need for secondary exposure (“retakes”). The purpose of this retrospective study was to assess the frequency of re-exposures in CBCT and to identify whether the parameters age, gender, and field of view have an influence on the re-exposure of the patient. Additionally, the causes of re-exposures were determined and categorized. METHODS: In a retrospective cohort study CBCT images of 4986 patients from the patient database from the Department of Oral Radiology, University Medical Center of the Johannes Gutenberg University, Mainz, Germany were included a…

A Neurosurgical Stratagem: Doing the Same with Less?

2017

Automatic detection of cervical cells in Pap-smear images using polar transform and k-means segmentation

2016

We introduce a novel method of cell detection and segmentation based on a polar transformation. The method assumes that the seed point of each candidate is placed inside the nucleus. The polar representation, built around the seed, is segmented using k-means clustering into one candidate-nucleus cluster, one candidate-cytoplasm cluster and up to three miscellaneous clusters, representing background or surrounding objects that are not part of the candidate cell. For assessing the natural number of clusters, the silhouette method is used. In the segmented polar representation, a number of parameters can be conveniently observed and evaluated as fuzzy memberships to the non-cell class, out of …

Measurement of three-dimensional mirror parameters by polarization imaging applied to catadioptric camera calibration

2008

International audience; We present a new efficient method for calibration of cata- dioptric sensors. The method is based on an accurate measurement of the three-dimensional parameters of the mirror through polariza- tion imaging. While inserting a rotating polarizer between the cam- era and the mirror, the system is automatically calibrated without any calibration patterns. Moreover, this method permits most of the constraints related to the calibration of catadioptric systems to be relaxed. We show that, contrary to our system, the traditional meth- ods of calibration are very sensitive to misalignment of the camera axis and the symmetry axis of the mirror. From the measurement of three-di…