scholarly journals Evaluation and Implementation of Otsu and Active Contour Segmentation in Contrast-Enhanced Cardiac CT Images

2021 ◽  
Vol 3 (2) ◽  
pp. 136-141
Author(s):  
Arvi Razanata ◽  
Prawito Prajitno ◽  
Djarwani Soeharso Soejoko
Keyword(s):  
Ct Scan ◽  
Active Contour ◽  
Cardiac Ct ◽  
The Body ◽  
Heart Volume ◽  
Contour Segmentation ◽  
Inter Observer Variability ◽  
Contrast Enhanced ◽  
Additional Image ◽  
Processing Techniques

The CT cardiac acquisition process is usually conducted by using an additional image with contrast medium that is injected inside the body and reconstructed by a radiologist using an integrated CT Scan software with the aim to find the morphology and volume dimension of the heart and coronary arteries. In fact, the data obtained from the hospital are raw data without segmented contour from a radiologist. For the purpose of automation, dataset is needed to be used as input data for further program development. This study is focused on the evaluation of the segmentation results of CT cardiac images using Otsu threshold and active contour algorithm with the aim to make a dataset for the heart volume quantification that can be used interactively as an alternative to integrated CT scan software. 2D contrast enhanced cardiac CT from 6 patients using image processing techniques was run on Matlab software. Of the 689 slices that was used, as many as (73.75 ± 19.41)%of CT cardiac slices have been segmented properly, (19.15 ± 19.61)%of the slices that were segmented included the spine bone, (1.36 ± 0.98)%of the slices did not include all region of the heart, (16.58 ± 15.26)%of the slices included other organs with the consistency from the measurement proven from inter-observer variability to produce r = 0,9941.The result is due to the geometry influence from the diameter of the patient’s body thickness that tends to be thin.

scholarly journals An Intelligent Baby Monitor with Automatic Sleeping Posture Detection and Notification

AI ◽  
2021 ◽  
Vol 2 (2) ◽  
pp. 290-306
Author(s):  
Tareq Khan
Keyword(s):  
Language Translation ◽  
Video Data ◽  
The Body ◽  
Night Vision ◽  
Monitoring Device ◽  
Peace Of Mind ◽  
Image Processing Techniques ◽  
Pose Detection ◽  
Processing Techniques ◽  
Monitoring Devices

Artificial intelligence (AI) has brought lots of excitement to our day-to-day lives. Some examples are spam email detection, language translation, etc. Baby monitoring devices are being used to send video data of the baby to the caregiver’s smartphone. However, the automatic understanding of the data was not implemented in most of these devices. In this research, AI and image processing techniques were developed to automatically recognize unwanted situations that the baby was in. The monitoring device automatically detected: (a) whether the baby’s face was covered due to sleeping on the stomach; (b) whether the baby threw off the blanket from the body; (c) whether the baby was moving frequently; (d) whether the baby’s eyes were opened due to awakening. The device sent notifications and generated alerts to the caregiver’s smartphone whenever one or more of these situations occurred. Thus, the caregivers were not required to monitor the baby at regular intervals. They were notified when their attention was required. The device was developed using NVIDIA’s Jetson Nano microcontroller. A night vision camera and Wi-Fi connectivity were interfaced. Deep learning models for pose detection, face and landmark detection were implemented in the microcontroller. A prototype of the monitoring device and the smartphone app were developed and tested successfully for different scenarios. Compared with general baby monitors, the proposed device gives more peace of mind to the caregivers by automatically detecting un-wanted situations.

The contrast-enhanced CT scan in the diagnosis of isodense subdural hematoma

1979 ◽  
Vol 50 (1) ◽  
pp. 64-69 ◽  
Author(s):  
Fong Y. Tsai ◽  
James E. Huprich ◽  
Hervey D. Segall ◽  
James S. Teal
Keyword(s):  
Cerebral Cortex ◽  
Ct Scan ◽  
Subdural Hematoma ◽  
Correct Diagnosis ◽  
Content Type ◽  
Subdural Hematomas ◽  
Contrast Enhanced Ct ◽  
Contrast Enhanced ◽  
Enhanced Ct ◽  
Fine Print

✓ The authors review 29 cases of surgically-proven isodense subdural hematomas examined by non-contrast and contrast-enhanced computerized tomography scans. Three types of isodense collections were noted: homogeneous isodense collections, mixed-density collections, and gravitational layering within subdural collections. Contrast enhancement within the cerebral cortex, cortical vessels, and subdural membranes led to the correct diagnosis in each case. Contrast-enhanced scans are essential for the evaluation of isodense subdural hematomas.

Quantification of Lymphedema in a Rat Model by 3D-Active Contour Segmentation by Magnetic Resonance Imaging

2012 ◽  
Vol 10 (1) ◽  
pp. 25-29 ◽  
Author(s):  
Tanja Sommer ◽  
Martin Meier ◽  
Frank Bruns ◽  
Reinhard Pabst ◽  
Gerhard Breves ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Rat Model ◽  
Active Contour ◽  
Resonance Imaging ◽  
Contour Segmentation

Lung Cancer Detection using Image Processing Techniques and its Classification

2021 ◽  
Vol 9 (9) ◽  
pp. 1578-1583
Author(s):  
Aishwarya .R
Keyword(s):  
Lung Cancer ◽  
Image Processing ◽  
Support Vector Machine ◽  
Cell Carcinoma ◽  
Mortality Rates ◽  
The Body ◽  
Support Vector ◽  
Lung Tumour ◽  
Image Processing Techniques ◽  
Processing Techniques

Abstract: Lung cancer has been a major contribution to mortality rates world-wide for many years now. There is a need for early diagnosis of lung cancer which if implemented, will help in reducing mortality rates. Recently, image processing techniques have been widely applied in various medical facilities for accurate detection and diagnosis of abnormality in the body images like in various cancers such as brain tumour, breast tumour and lung tumour. This paper is a development of an algorithm based on medical image processing to segment the lung tumour in CT images due to the lack of such algorithms and approaches used to detect tumours. The work involves the application of different image processing tools in order to arrive at the desired result when combined and successively applied. The segmentation system comprises different steps along the process. First, Image preprocessing is done where some enhancement is done to enhance and reduce noise in images. In the next step, the different parts in the images are separated to be able to segment the tumour. In this phase threshold value was selected automatically. Then morphological operation (Area opening) is implemented on the thresholded image. Finally, the lung tumour is accurately segmented by subtracting the opened image from the thresholded image. Support Vector Machine (SVM) classifier is used to classify the lung tumour into 4 different types: Adenocarcinoma(AC), Large Cell Carcinoma(LCC) Squamous Cell Carcinoma(SCC), and No tumour (NT). Keywords: Lung tumour; image processing techniques; segmentation; thresholding; image enhancement; Support Vector Machine; Machine learning;

scholarly journals Computer-Assisted Segmentation of Videocapsule Images Using Alpha-Divergence-Based Active Contour in the Framework of Intestinal Pathologies Detection

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
L. Meziou ◽  
A. Histace ◽  
F. Precioso ◽  
O. Romain ◽  
X. Dray ◽  
...  
Keyword(s):  
Gastrointestinal Tract ◽  
Active Contour ◽  
Standard Technique ◽  
Poor Quality ◽  
Computer Assisted ◽  
Contour Segmentation ◽  
Semiautomatic Segmentation ◽  
Different Types ◽  
Statistical Similarity ◽  
Wireless Capsule

Visualization of the entire length of the gastrointestinal tract through natural orifices is a challenge for endoscopists. Videoendoscopy is currently the “gold standard” technique for diagnosis of different pathologies of the intestinal tract. Wireless capsule endoscopy (WCE) has been developed in the 1990s as an alternative to videoendoscopy to allow direct examination of the gastrointestinal tract without any need for sedation. Nevertheless, the systematic postexamination by the specialist of the 50,000 (for the small bowel) to 150,000 images (for the colon) of a complete acquisition using WCE remains time-consuming and challenging due to the poor quality of WCE images. In this paper, a semiautomatic segmentation for analysis of WCE images is proposed. Based on active contour segmentation, the proposed method introduces alpha-divergences, a flexible statistical similarity measure that gives a real flexibility to different types of gastrointestinal pathologies. Results of segmentation using the proposed approach are shown on different types of real-case examinations, from (multi)polyp(s) segmentation, to radiation enteritis delineation.

scholarly journals Is CT Angiogram of the Abdominal Vessels Needed following the Diagnosis of Ischemic Colitis? A Multicenter Community Study

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Muhammed Sherid ◽  
Salih Samo ◽  
Samian Sulaiman ◽  
Husein Husein ◽  
Sankara N. Sethuraman ◽  
...  
Keyword(s):  
Ct Scan ◽  
Ischemic Colitis ◽  
Celiac Trunk ◽  
Ct Angiogram ◽  
Contrast Enhanced Ct ◽  
Contrast Enhanced ◽  
Enhanced Ct ◽  
Group 3 ◽  
Group 5 ◽  
Atherosclerotic Changes

Background. CT angiogram is frequently obtained after diagnosis of ischemic colitis (IC). Aims. To investigate the vascular findings of CT angiogram as compared to contrast-enhanced CT scan and whether this modality changes the management or prognosis of IC. Methods. We conducted a retrospective analysis of patients with IC from 2007 to 2013. Results. CT angiogram was performed in 34 patients (28.81%), whereas contrast-enhanced CT scan was performed in 54 patients (45.76%). In CT angiogram group, 8 patients (23.5%) had atherosclerotic changes. Stenosis was found in 12 patients (35.3%) (9: celiac trunk, 3: SMA). Among this group, one patient underwent colectomy and another underwent angioplasty of the celiac trunk who died within 30 days. Among contrast-enhanced CT scan group, 5 patients (9.3%) had atherosclerotic changes. Stenosis was found in 5 patients (9.3%) (3: celiac trunk, 1: SMA, and 1: IMA). Among this group, 3 patients had colectomy and one died within 30 days. There was no statistical difference between both groups in all vascular findings except the stenosis which was higher in CT angiogram group (P=0.0025). Neither the need for surgery nor all-cause mortality was different between both groups. Conclusion. CT angiogram did not provide any useful findings that altered the management or the prognosis of IC.

scholarly journals The Effect of Contrast-enhanced Computed Tomography (CT) Scans on the Calculated Dose of Radiotherapy in a Thorax Phantom

2021 ◽  
Vol In Press (In Press) ◽  
Author(s):  
Athar Ehtiati ◽  
Payman Hejazi ◽  
Mohsen Bakhshandeh ◽  
Ali Jabbary Arfaee ◽  
Eftekhar Rajab Bolookat ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Contrast Media ◽  
Ct Scan ◽  
Treatment Planning ◽  
Tumor Volume ◽  
Ct Scans ◽  
Contrast Enhanced ◽  
Enhanced Ct ◽  
Enhanced Computed Tomography ◽  
Contrast Enhanced Computed Tomography

Background: Despite the benefits of contrast-enhanced computed tomography (CT) scans in better tumor volume delineation, it can affect the accuracy of dose calculation in radiation therapy. This study examined this effect on a thorax phantom. Objectives: The influence of different variables including the concentrations of the Visipaque contrast media, tumor sizes, and CT scan energies on the dose measurement was examined. Methods: Transparent cylinders containing the contrast media were inserted in the lung area of the phantom and the CT scans were made. Non-enhanced CT scans were also acquired. Treatment planning using 2 opposite fields was performed on the CT scans and the doses were calculated in the treatment planning system. The results of the 2 sets of enhanced and non-enhanced CT scans were compared. Results: The correlation between concentration and the percentage of mean dose of the tumor volume was significant in 2 of the tumor sizes. The differences in the mean doses of the 2 plans were examined and more than 3% increase was observed in higher concentrations of the contrast media. Conclusions: According to this study, the suitable concentration of the contrast media administered and the CT scan energy should be considered. This would help to decrease the discrepancies between the calculated and delivered dose in radiotherapy treatments to a clinically acceptable level. The importance of time delays for CT scans after administration of the contrast media is emphasized.

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