scholarly journals Morphological characteristics of X-ray thorax images of COVID-19 patients using the Bradley thresholding segmentation

2021 ◽  
Vol 24 (2) ◽  
pp. 1074
Author(s):  
Retno Supriyanti ◽  
Muhammad Alqaaf ◽  
Yogi Ramadhani ◽  
Haris B. Widodo
Keyword(s):  
Detection System ◽  
Screening Method ◽  
Morphological Characteristics ◽  
Segmentation Method ◽  
Resonance Imaging ◽  
X Ray ◽  
Chest Radiology ◽  
Magnetic Resonance Imaging Mri ◽  
Health Care Centers ◽  
Aided Diagnosis

The coronavirus disease 2019 (COVID-19) pandemic has made test screening much needed. Currently, the most commonly used is the swab type. Although in fact, there is also a screening method with chest radiology. The purpose of this study is to develop a COVID-19 early detection system based on X-ray images of the patient's thorax in the form of a computer-aided diagnosis. This case is based on the fact that X-ray modalities are available in several health care centers in Indonesia, compared to other modalities such as computed tomography (CT) scan or magnetic resonance imaging (MRI). In this paper, we emphasize the X-ray thorax image segmentation process to explore the morphological information of the thorax. We use the Bradley thresholding segmentation method. The results obtained are promising to be further developed with a performance percentage of 73.33% for the thorax for COVID-19 patients and 54% for the thorax for normal patients.

scholarly journals Brain Structures Segmentation by using Statistical Models

2017 ◽  
Vol 1 (3) ◽  
pp. 59
Author(s):  
Abdelfettah Meziane ◽  
Saïd MAHMOUDI ◽  
Mohammed Amine CHIKH
Keyword(s):  
Automatic Segmentation ◽  
Brain Structures ◽  
Segmentation Method ◽  
Resonance Imaging ◽  
Active Appearance Models ◽  
Active Shape Models ◽  
Shape Models ◽  
Appearance Models ◽  
Magnetic Resonance Imaging Mri ◽  
Aided Diagnosis

Automatic segmentation of brain structures is a fundamental step for quantitative analysis of images in many brain’s pathologies such as Alzheimer’s, brain’s tumors or multiple sclerosis. The large variation of brain structures requires the development of efficient and specific methods, often by using Magnetic Resonance Imaging (MRI) modality. The goal of our work is to implement an automatic brain’s structures segmentation method that uses the active shape models (ASM) and active appearance models (AAM) techniques. Another goal of this work is to compare the performances of these segmentation approaches, and also to evaluate their use in a computer aided diagnosis tools and to compare their performances.

scholarly journals Deep learning based MRI contrast synthesis using full volume prediction

2021 ◽  
Author(s):  
Jose V Manjon ◽  
Jose E Romero ◽  
Pierrick Coupé
Keyword(s):  
Three Dimensional ◽  
Patient Comfort ◽  
Segmentation Method ◽  
Resonance Imaging ◽  
Complementary Information ◽  
Mri Contrast ◽  
Ambiguity Reduction ◽  
Magnetic Resonance Imaging Mri ◽  
Time Limitations ◽  
Full Volume

Abstract In Magnetic Resonance Imaging (MRI), depending on the image acquisition settings, a large number of image types or contrasts can be generated showing complementary information of the same imaged subject. This multi-spectral information is highly beneficial since can improve MRI analysis tasks such as segmentation and registration, thanks to pattern ambiguity reduction. However, the acquisition of several contrasts is not always possible due to time limitations and patient comfort constraints. Contrast synthesis has emerged recently as an approximate solution to generate other image types different from those acquired originally. Most of the previously proposed methods for contrast synthesis are slice-based which result in intensity inconsistencies between neighbor slices when applied in 3D. We propose the use of a 3D convolutional neural network (CNN) capable of generating T2 and FLAIR images from a single anatomical T1 source volume. The proposed network is a 3D variant of the UNet that processes the whole volume at once breaking with the inconsistency in the resulting output volumes related to 2D slice or patch-based methods. Since working with a full volume at once has a huge memory demand we have introduced a spatial-to-depth and a reconstruction layer that allows working with the full volume but maintain the required network complexity to solve the problem. Our approach enhances the coherence in the synthesized volume while improving the accuracy thanks to the integrated three-dimensional context-awareness. Finally, the proposed method has been validated with a segmentation method, thus demonstrating its usefulness in a direct and relevant application.

scholarly journals The Assessment of the Condition of Knee Joint Surfaces with Acoustic Emission Analysis

Sensors ◽  
2021 ◽  
Vol 21 (19) ◽  
pp. 6495
Author(s):  
Bartłomiej Sawaryn ◽  
Natalia Piaseczna ◽  
Szymon Sieciński ◽  
Rafał Doniec ◽  
Konrad Duraj ◽  
...  
Keyword(s):  
Knee Joint ◽  
Knee Injury ◽  
Knee Joints ◽  
Resonance Imaging ◽  
Emission Analysis ◽  
X Ray ◽  
Joint Surfaces ◽  
Magnetic Resonance Imaging Mri ◽  
Leg Movements ◽  
Acoustic Emission Analysis

The knee joint, being the largest joint in the human body, is responsible for a great percentage of leg movements. The diagnosis of the state of knee joints is usually based on X-ray scan, ultrasound imaging, computerized tomography (CT), magnetic resonance imaging (MRI), or arthroscopy. In this study, we aimed to create an inexpensive, portable device for recording the sound produced by the knee joint, and a dedicated application for its analysis. During the study, we examined fourteen volunteers of different ages, including those who had a knee injury. The device effectively enables the recording of the sounds produced by the knee joint, and the spectral analysis used in the application proved its reliability in evaluating the knee joint condition.

scholarly journals Chemical Modifications of Porous Shape Memory Polymers for Enhanced X-ray and MRI Visibility

Molecules ◽  
2020 ◽  
Vol 25 (20) ◽  
pp. 4660
Author(s):  
Grace K. Fletcher ◽  
Landon D. Nash ◽  
Lance M. Graul ◽  
Lindy K. Jang ◽  
Scott M. Herting ◽  
...  
Keyword(s):  
Shape Memory ◽  
Medical Devices ◽  
Shape Memory Polymer ◽  
Shape Memory Polymers ◽  
Tissue Scaffolds ◽  
Resonance Imaging ◽  
Clinical Imaging ◽  
X Ray ◽  
Device Development ◽  
Magnetic Resonance Imaging Mri

The goal of this work was to develop a shape memory polymer (SMP) foam with visibility under both X-ray and magnetic resonance imaging (MRI) modalities. A porous polymeric material with these properties is desirable in medical device development for applications requiring thermoresponsive tissue scaffolds with clinical imaging capabilities. Dual modality visibility was achieved by chemically incorporating monomers with X-ray visible iodine-motifs and MRI visible monomers with gadolinium content. Physical and thermomechanical characterization showed the effect of increased gadopentetic acid (GPA) on shape memory behavior. Multiple compositions showed brightening effects in pilot, T1-weighted MR imaging. There was a correlation between the polymeric density and X-ray visibility on expanded and compressed SMP foams. Additionally, extractions and indirect cytocompatibility studies were performed to address toxicity concerns of gadolinium-based contrast agents (GBCAs). This material platform has the potential to be used in a variety of medical devices.

Complete Palmar Dislocation of the Lunate in Rheumatoid Arthritis

1996 ◽  
Vol 21 (3) ◽  
pp. 384-387 ◽  
Author(s):  
M. ARNER ◽  
K. JONSSON ◽  
P. ASPENBERG
Keyword(s):  
Bone Structure ◽  
Bone Cells ◽  
X Rays ◽  
Resonance Imaging ◽  
Rheumatoid Patient ◽  
X Ray ◽  
Normal Bone ◽  
Cellular Events ◽  
Magnetic Resonance Imaging Mri ◽  
Mri Changes

We report a case of complete palmar dislocation of the lunate in a rheumatoid patient. X-rays showed a normal bone structure of the lunate without sclerosis or collapse and on MRI an almost normal signal intensity was found. The lunate was removed. Histological examination showed complete necrosis of both marrow and bone cells, and tetracycline labelling showed no fluorescence. This case illustrates that neither X-ray nor magnetic resonance imaging (MRI) can detect complete bone necrosis. When X-ray or MRI changes do occur, these are indications of cellular events following some degree of spontaneous revascularization.

scholarly journals Juxtacortical Clavicular Chondrosarcoma: Diagnostic Dilemmas: Case Report and Review of Literature

2013 ◽  
Vol 7 ◽  
pp. CMO.S10542 ◽  
Author(s):  
E.I. Efremidou ◽  
A. Oikonomou ◽  
E. Pavlidou ◽  
G. Drosos ◽  
A. Koutsopoulos ◽  
...  
Keyword(s):  
Bone Scan ◽  
Three Dimensional ◽  
Accurate Diagnosis ◽  
Review Of Literature ◽  
Resonance Imaging ◽  
X Ray ◽  
Cartilaginous Tumor ◽  
Accurate Preoperative Diagnosis ◽  
Chest X Ray ◽  
Magnetic Resonance Imaging Mri

Juxtacortical chondrosarcoma is a rare primary malignant cartilaginous tumor accounting for 0.2% of all bone tumors. Wide surgical resection is the treatment of choice for juxtacortical chondrosarcomas. Accurate preoperative diagnosis is important in ensuring appropriate management, staging, and treatment of the patient. A combination of radiographs, three-dimensional imaging with computerized tomography (CT) scan and magnetic resonance imaging (MRI) can typically allow accurate diagnosis of juxtacortical chondrosarcomas. Bone scan and chest x-ray or CT chest scans are indicated for appropriate staging of the patient. Pet scan, ultrasound, bone scan, etc. are not typically needed for the diagnosis. Certainly, pulmonary imaging and bone scan are required for staging and could be commented upon.

scholarly journals A Case Of Atypical Presentation of Thoracic Osteomyelitis & Paraspinal Abscess

2020 ◽  
Vol 11 (2) ◽  
Author(s):  
Utkarsh Acharya
Keyword(s):  
Bone Scan ◽  
Medical Intervention ◽  
Chief Complaint ◽  
Resonance Imaging ◽  
Anterior Portion ◽  
X Ray ◽  
Right Lobe ◽  
Magnetic Resonance Imaging Mri ◽  
The Right ◽  
Paraspinal Abscess

Here presented is a case involving a 44-year-old man with a chief complaint of sharp lateral right-sided rib pain with notable radiation to the anterior portion of the thorax and minor radiation around the lateral back. The etiology of the pain and radiculopathy, which was initially attributed to a right-sided rib fracture, was later accurately credited to a paraspinal abscess discovered on a lateral X-ray of the thoracic spine. Subsequently, studies including Magnetic Resonance Imaging (MRI), Computed Tomography (CT), and bone scan all confirmed the diagnosis of a paraspinal abscess between the right lobe and its neighboring T9 and T10 vertebrae. The mass was biopsied and methicillin sensitive Staphylococcus aureus was isolated. Appropriate surgical and medical intervention was possible due to the early diagnosis of the abscess.

scholarly journals Deep Learning-Based Acute Ischemic Stroke Lesion Segmentation Method on Multimodal MR Images Using a Few Fully Labeled Subjects

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Bin Zhao ◽  
Zhiyang Liu ◽  
Guohua Liu ◽  
Chen Cao ◽  
Song Jin ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
Acute Ischemic Stroke ◽  
Segmentation Method ◽  
Lesion Segmentation ◽  
Resonance Imaging ◽  
Mr Images ◽  
Dice Coefficient ◽  
Automatic Methods ◽  
Stroke Lesion ◽  
Magnetic Resonance Imaging Mri

Acute ischemic stroke (AIS) has been a common threat to human health and may lead to severe outcomes without proper and prompt treatment. To precisely diagnose AIS, it is of paramount importance to quantitatively evaluate the AIS lesions. By adopting a convolutional neural network (CNN), many automatic methods for ischemic stroke lesion segmentation on magnetic resonance imaging (MRI) have been proposed. However, most CNN-based methods should be trained on a large amount of fully labeled subjects, and the label annotation is a labor-intensive and time-consuming task. Therefore, in this paper, we propose to use a mixture of many weakly labeled and a few fully labeled subjects to relieve the thirst of fully labeled subjects. In particular, a multifeature map fusion network (MFMF-Network) with two branches is proposed, where hundreds of weakly labeled subjects are used to train the classification branch, and several fully labeled subjects are adopted to tune the segmentation branch. By training on 398 weakly labeled and 5 fully labeled subjects, the proposed method is able to achieve a mean dice coefficient of 0.699 ± 0.128 on a test set with 179 subjects. The lesion-wise and subject-wise metrics are also evaluated, where a lesion-wise F1 score of 0.886 and a subject-wise detection rate of 1 are achieved.

scholarly journals Using Diagnostic Ultrasound to Support the Diagnose Sarcopenia in Older Adults: A Systematic Review

2021 ◽  
Vol 5 (Supplement_1) ◽  
pp. 996-996
Author(s):  
Edgar Vieira ◽  
Lily Charles ◽  
Monica Cortes ◽  
Tabitha Lees
Keyword(s):  
Older Adults ◽  
Normative Data ◽  
Muscle Thickness ◽  
Diagnostic Ultrasound ◽  
Pennation Angle ◽  
Resonance Imaging ◽  
Cross Sectional ◽  
X Ray ◽  
Magnetic Resonance Imaging Mri ◽  
Head Neck

Abstract Dual-energy x-ray absorptiometry (DXA) is currently the gold standard for diagnosing loss of muscle mass in older adults (a component of sarcopenia diagnosis). Magnetic resonance imaging (MRI) and computed tomography (CT) have also been used successfully. Due to elevated costs, limited access, exposure to radiation, and increased difficulty of operation, other methods have been explored as alternatives. We reviewed the literature on the use of diagnostic ultrasound to assist in the diagnose sarcopenia in older adults by searching MEDLINE, Embase, and CINAHL using a variation of terms related to “ultrasound”, “sarcopenia”, and “older adults”. We included studies that included older adults over the age of 60. Eighteen studies were included after screening for eligibility and conducting full-text reviews. The most common transducer head frequency utilized in the studies were 5-12 and 8 MHz (three studies each), followed by 5, 6, and 7.5 MHz (two studies each). The most common musculature examined was anterior thigh musculature, followed by muscles of the lower leg, upper extremity, abdominals, and head/neck. Measurements most taken were muscle thickness/cross sectional area (18 studies), followed by muscle echogenicity (9 studies), and pennation angle (3 studies). Ultrasound is a reliable and valid tool to examine muscle thickness to assist in diagnosing sarcopenia. However, echogenicity measures of a muscle were not reliable. Further research is needed with increased sample size and variance amongst subjects to generalize and create normative data. In addition, standardized protocols for the use of ultrasound to assist in the diagnosing sarcopenia need to be established.

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