Kjersti Engan

Kjersti Engan
University of Stavanger (UiS) · Department of Electrical engineering and Computer science

Professor

About

120
Publications
19,807
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5,235
Citations
Introduction
Kjersti Engan is currently a full professor with at the Department of Electrical engineering and Computer science, University of Stavanger (UiS), Norway. She is a part of the Biomedical data analysis group at UiS. Her research interests are in signal and image processing, and especially: - Biomedical signal and image processing, analysis and classification - Dictionary learning for sparse signal and image representation

Publications

Publications (120)
Conference Paper
Full-text available
In recent years, thermal imaging has been used in numerous applications due to its ability to capture and visualize the thermal radiation emitted by objects. Thermal cameras can be employed as non-invasive systems for detecting variations in temperatures while protecting privacy in case people are involved. Due to this, thermal imaging is especiall...
Article
Time is a fundamental factor during stroke treatments. A fast, automatic approach that segments the ischemic regions helps treatment decisions. In clinical use today, a set of color-coded parametric maps generated from computed tomography perfusion (CTP) images are investigated manually to decide a treatment plan. We propose an automatic method bas...
Preprint
Full-text available
Time is a fundamental factor during stroke treatments. A fast, automatic approach that segments the ischemic regions helps treatment decisions. In clinical use today, a set of color-coded parametric maps generated from computed tomography perfusion (CTP) images are investigated manually to decide a treatment plan. We propose an automatic method bas...
Article
Whole Slide Images (WSI) are widely used in histopathology for research and the diagnosis of different types of cancer. The preparation and digitization of histological tissues leads to the introduction of artifacts and variations that need to be addressed before the tissues are analyzed. WSI preprocessing can significantly improve the performance...
Preprint
Full-text available
Multiple instance learning (MIL) is a type of weakly supervised learning where multiple instances of data with unknown labels are sorted into bags. Since knowledge about the individual instances is incomplete, labels are assigned to the bags containing the instances. While this method fits diverse applications were labelled data is scarce, it lacks...
Article
Full-text available
The most common type of bladder cancer is urothelial carcinoma, which is among the cancer types with the highest recurrence rate and lifetime treatment cost per patient. Diagnosed patients are stratified into risk groups, mainly based on grade and stage. However, it is well known that correct grading of bladder cancer suffers from intra-and interob...
Article
The field of digital histopathology has seen incredible growth in recent years. Digital pathology is becoming a relevant tool in healthcare, industrial and research sectors to reduce the saturation of pathology departments and improve the productivity of pathologists by increasing diagnostic accuracy and reducing turnaround times. Artificial Intell...
Article
Full-text available
Objective: Computed tomography (CT) scan is a fast and widely used modality for early assessment in patients with symptoms of a cerebral ischemic stroke. CT perfusion (CTP) is often added to the protocol and is used by radiologists for assessing the severity of the stroke. Standard parametric maps are calculated from the CTP datasets. Based on par...
Preprint
Full-text available
More than 13 million people suffer from ischemic cerebral stroke worldwide each year. Thrombolytic treatment can reduce brain damage but has a narrow treatment window. Computed Tomography Perfusion imaging is a commonly used primary assessment tool for stroke patients, and typically the radiologists will evaluate resulting parametric maps to estima...
Article
Full-text available
Abstract Background Fresh stillbirths (FSB) and very early neonatal deaths (VEND) are important global challenges with 2.6 million deaths annually. The vast majority of these deaths occur in low- and low-middle income countries. Assessment of the fetal well-being during pregnancy, labour, and birth is normally conducted by monitoring the fetal hear...
Conference Paper
More than 13 million people suffer from ischemic cerebral stroke worldwide each year. Thrombolytic treatment can reduce brain damage but has a narrow treatment window. Computed Tomography Perfusion imaging is a commonly used primary assessment tool for stroke patients, and typically the radiologists will evaluate resulting parametric maps to estima...
Conference Paper
Full-text available
Supervised learning of convolutional neural networks (CNN) used for image classification and segmentation has produced state-of-the-art results, including in many medical image applications. In the medical field, making ground truth labels would typically require an expert opinion , and a common problem is the lack of labeled data. Consequently, th...
Article
Full-text available
Objective: Birth asphyxia is one of the leading causes of neonatal deaths. A key for survival is performing immediate and continuous quality newborn resuscitation. A dataset of recorded signals during newborn resuscitation, including videos, has been collected in Haydom, Tanzania, and the aim is to analyze the treatment and its effect on the newbo...
Article
Background and objective: Early neonatal death is a worldwide challenge with 1 million newborn deaths every year. The primary cause of these deaths are complications during labour and birth asphyxia. The majority of these newborns could have been saved with adequate resuscitation at birth. Newborn resuscitation guidelines recommend immediate dryin...
Article
Full-text available
In pathology labs worldwide, we see an increasing number of tissue samples that need to be assessed without the same increase in the number of pathologists. Computational pathology, where digital scans of histological samples called whole-slide images (WSI) are processed by computational tools, can be of help for the pathologists and is gaining res...
Article
Full-text available
This article considers the analysis of complex monitored health data, where often one or several signals are reflecting the current health status that can be represented by a finite number of states, in addition to a set of covariates. In particular, we consider a novel application of a non-parametric state intensity regression method in order to s...
Preprint
Full-text available
Correct treatment of urothelial carcinoma patients is dependent on accurate grading and staging of the cancer tumour. This is determined manually by a pathologist by examining the histological whole-slide images (WSI). The large size of these images makes this a time-consuming and challenging task. The WSI contain a variety of tissue types, and a m...
Article
Full-text available
Objective: Birth asphyxia is a major newborn mortality problem in low-resource countries. International guideline provides treatment recommendations; however, the importance and effect of the different treatments are not fully explored. The available data is collected in Tanzania, during newborn resuscitation, for analysis of the resuscitation act...
Article
Full-text available
Aim: Our aim was to automatically estimate the blood velocity in coronary arteries using cine X-ray angiographic sequence. Estimating the coronary blood velocity is a key approach in investigating patients with angina pectoris and no significant coronary artery disease. Blood velocity estimation is central in assessing coronary flow reserve. Method...
Article
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Out-of-hospital cardiac arrest (OHCA) is recognized as a global mortality challenge, and digital strategies could contribute to increase the chance of survival. In this paper, we investigate if cardiopulmonary resuscitation (CPR) quality measurement using smartphone video analysis in real-time is feasible for a range of conditions. With the use of...
Article
Texture feature extraction is an important task in image processing and computer vision. Typical applications include automated inspection, image retrieval or medical analysis. In this paper we propose a noise robust and rotation invariant approach to texture feature analysis and classification. The proposed framework is based on a simple texture f...
Article
Full-text available
Aim: An automatic resuscitation rhythm annotator (ARA) would facilitate and enhance retrospective analysis of resuscitation data, contributing to a better understanding of the interplay between therapy and patient response. The objective of this study was to define, implement, and demonstrate an ARA architecture for complete resuscitation episodes...
Article
Newborn deaths are reported to be caused mainly by birth asphyxia. Information learned from ventilation and other treatment could help increase survival rate of newborns in need of resuscitation. Characteristics of manual bag-mask ventilation have been studied in our previous works. However, other resuscitation activities could have important impac...
Article
Sparse representation and Dictionary learning have attracted a lot of research attention in the last couple of decades and have provided state of the art results in many fields such as denoising, classification, inpainting and compression. However, applying general dictionary learning such as Method of Optimal Directions and Recursive Least Squares...
Conference Paper
Full-text available
Telephone assisted guidance between dispatcher and bystander providing cardiopulmonary resuscitation (CPR) can improve the quality of the CPR provided to patients suffering from cardiac arrest. Our research group has earlier proposed a system for communication and feedback of the compression rate to the dispatcher through a smartphone application....
Conference Paper
Sparse approximation of signals using often redundant and learned data dependent dictionaries has been successfully used in many applications in signal and image processing the last couple of decades. Finding the optimal sparse approximation is in general an NP complete problem and many suboptimal solutions have been proposed: greedy methods like M...
Article
Methods: The dataset consisted of 1631 3- second ECG segments with clinical rhythm annotations, obtained from 298 out-of-hospital cardiac arrest patients. 47 wavelet and time domain based features were computed from the ECG. Features were selected using a wrapper-based feature selection architecture. Classifiers based on Bayesian decision theory,...
Article
Full-text available
Background Out-of-hospital cardiac arrest is a life threatening situation where the first person performing cardiopulmonary resuscitation (CPR) most often is a bystander without medical training. Some existing smartphone apps can call the emergency number and provide for example global positioning system (GPS) location like Hjelp 113-GPS App by the...
Conference Paper
This paper describes how to construct a probability map using sparse representation and dictionary learning to indicate the probability of each optic disk pixel of belonging to the optic cup. This probability map will be used in the future as input to a method for automatically detecting glaucoma from color fundus images. The probability map was ob...
Conference Paper
Objectives: Clinical intervention for non-breathing newborns due to birth asphyxia needs to be conducted within the first minute of life. The responses of the babies are affected by complicated interactions between physiological conditions of the newborns and the combination of various clinical treatments, e.g., drying thoroughly, stimulation, manu...
Article
Aim: Resuscitation guidelines recommend different treatments depending on the patient's cardiac rhythm. Rhythm interpretation is a key tool to retrospectively evaluate and improve the quality of treatment. Manual rhythm annotation is time consuming and an obstacle for handling large resuscitation datasets efficiently. The objective of this study w...
Article
Objectives: Birth asphyxia is a condition where a fetus suffers from lack of oxygen during birth. Intervention by manual ventilation should start within one minute after birth. Bag-mask resuscitators are commonly used in situations where ventilation is provided by a single health care worker. Due to a high complexity of interactions between physio...
Article
Some important eye diseases, like macular degeneration or diabetic retinopathy, can induce changes visible on the retina, for example as lesions. Segmentation of lesions or extraction of textural features from the fundus images are possible steps towards automatic detection of such diseases which could facilitate screening as well as provide suppor...
Conference Paper
Retinal blood vessels are considered as being interference on the retinal images for the task of detecting significant features of the most frequent eye diseases. If these blood vessel structures could be suppressed, it might lead to a more accurate segmentation of retinal lesions as well as a better extraction of textural features to be used for p...
Article
This work investigates discrimination capabilities in the texture of fundus images to differentiate between pathological and healthy images. For this purpose, the performance of Local Binary Patterns (LBP) as a texture descriptor for retinal images has been explored and compared with other descriptors such as LBP filtering (LBPF) and local phase qu...
Article
Full-text available
Aims . The correspondence between the localization and morphology of ischemic scars and the infarct related artery (IRA) by use of cardiac magnetic resonance imaging and a novel automatic postprocessing method. Methods and Results . Thirty-four patients with one-year-old single IRA myocardial infarction were examined. Endocardium, epicardium, and t...
Conference Paper
This work focuses on differentiating between pathological and healthy fundus images. The goal is to distinguish between diabetic retinopathy (DR), age-related macular degeneration (AMD) and normal images by analysing the texture of the retina background. Local Binary Patterns (LBP) are used as texture descriptors. The two class problems DR vs. norm...
Conference Paper
In this study we present a method for segmenting microvascular obstruction in patients with myocardial infarction. The presence of microvascular obstruction is an important prognostic indicator. In late enhanced cardiac magnetic resonance images scar will have very high signal intensity while areas of microvascular obstruction will appear with low...
Conference Paper
Dictionary learning and Sparse representation of signals and images has been a hot topic for the past decade and aims to help find the sparsest representation for the signal(s) at hand. Typically, the Dictionary learning process involves finding a large number of free variables. Also, the resulting dictionary in general does not have a specific str...
Article
The relationship between the heart rate of ventricular tachycardia (VT) and the transmurality of ischemic scars was assessed by a new semiautomatic coordinate-based analysis of late gadolinium-enhanced cardiac magnetic resonance (LGE-CMR) images. Twenty patients assessed by LGE-CMR before implantation of implantable cardioverter defibrillator (ICD)...
Article
Introduction: Patients surviving myocardial infarction (MI) can be divided into high and low arrhythmic risk groups. Distinguishing between these two groups is of crucial importance since the high-risk group has been shown to benefit from implantable cardioverter defibrillator insertion; a costly surgical procedure with potential complications and...
Article
Full-text available
Dementia is an evolving challenge in society, and no disease-modifying treatment exists. Diagnosis can be demanding and MR imaging may aid as a noninvasive method to increase prediction accuracy. We explored the use of 2D local binary pattern (LBP) extracted from FLAIR and T1 MR images of the brain combined with a Random Forest classifier in an att...
Article
This paper presents a novel method for the identification of myocardial regions associated with increased risk of life threatening arrhythmia in patients with healed myocardial infarction assessed by late enhanced gadolinium magnetic resonance images. A probability mapping technique is used to create images where each pixel value corresponds to the...
Conference Paper
Birth asphyxia is one of the leading causes of newborn deaths in low resource settings. In non-breathing newborns, ventilation should commence within the first minute after birth. Ventilation signals were studied and parameterized to reflect the characteristics of the provided ventilation. The effectiveness of ventilation was characterized by chang...
Conference Paper
Full-text available
In this paper we improve image segmentation based on texture properties. The already good results achieved using learned dictionaries and Gaussian smoothing are improved by minimizing an energy function that has the form of a Potts model. The proposed \(\alpha \)-erosion method is a greedy method that essentially relabels the pixels one by one and...
Conference Paper
In order to monitor the cardiac arrest patients response to therapy, there is a need for methods that can reliably interpret the different types of cardiac rhythms that can occur during a resuscitation episode. These rhythms can be categorized to five groups; ventricular tachycardia, ventricular fibrillation, pulseless electrical activity, asystole...
Article
Neonatal mortality due to birth asphyxia in low-resource countries is a global problem. During the first minutes immediately after birth, healthcare personnel need to resuscitate non-breathing babies by effective positive pressure ventilations. Currently, an increase in heart rate is thought to be the most important indicator of successful manual b...
Article
Current methods for the estimation of infarct size by late-enhanced cardiac magnetic imaging are based upon 2D analysis that first determines the size of the infarction in each slice, and thereafter adds the infarct sizes from each slice to generate a volume. We present a novel, automatic 3D method that estimates infarct size by a simultaneous anal...