
Prabal PoudelPhilips | Philips · Philips Healthcare
Prabal Poudel
Doctor of Philosophy
About
20
Publications
4,284
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174
Citations
Citations since 2017
Introduction
Prabal Poudel is a Scientist at Philips, Hamburg Germany. Prabal does research in Medical Image Processing specially in Ultrasound and Computed Tomography domain using current Machine and Deep Learning approaches.
Additional affiliations
January 2017 - July 2019
November 2015 - April 2016
Publications
Publications (20)
L Ma D Su D Qin- [...]
Michael Friebe
Treating of cancer is an important task e.g. in the liver which is one of the solid organs with high incident of tumor. Due to the technical improvement on biomedical systems and minimal invasive therapies currently microwave ablation (MWA) therapy as an invasive minimal therapy gets a lot of attention for destroying the cancer cells in its locatio...
This work focuses on investigating an optimal foetal heart rate (FHR) signal segment to be considered for automatic cardiotocographic (CTG) classification. The main idea is to evaluate a set of signal segments of different length and location based on their classification performance. For this purpose, we employ a feature extraction operation based...
Ultrasound (US) is an affordable and important imaging modality in medical imaging without potential hazards for patients and medical practitioners as compared to computed tomography (CT), magnetic resonance imaging (MRI), nuclear imaging, etc. Texture classification of anatomical structures in US images is an essential step for disease diagnosis a...
Ultrasound (US) imaging is one of the most cost-effective imaging modality that utilizes sound waves for generating medical images of anatomical structure. However, the presence of speckle noise and low contrast in the US images makes it difficult to use for proper classification of anatomical structures in clinical scenarios. Hence, it is importan...
Digital pathology can be thought of as a model composed of 3 main elements; classification algorithm, Graphical User Interface (GUI) and the pathologists. Currently there is only a one way interaction from the classification algorithm to the pathologist. This paper, proposes an additional backward path which is a new feedback-based method, aimed to...
The thyroid is one of the largest endocrine glands in the human body, which is involved in several body mechanisms like controlling protein synthesis, use of energy sources, and controlling the body’s sensitivity to other hormones. Thyroid segmentation and volume reconstruction are hence essential to diagnose thyroid related diseases as most of the...
Texture analysis is an important topic in Ultrasound (US) image analysis for structure segmentation and tissue classification. In this work a novel approach for US image texture feature extraction is presented. It is mainly based on parametrical modelling of a signal version of the US image in order to process it as data resulting from a dynamical...
The thyroid is one of the largest endocrine glands in the human body, which is involved in several body mechanisms like controlling protein synthesis and the body's sensitivity to other hormones and use of energy sources. Hence, it is of prime importance to track the shape and size of thyroid over time in order to evaluate its state. Thyroid segmen...
The classification of thyroid and non-thyroid regions in Ultrasound (US) images is of prime importance to the medical community as changes in the thyroid shape, size, and volume diagnosis can be used to diagnose thyroid disorders and improve calculation of activities for radioiodine therapy of thyroid diseases. An alteration in hormones leads to di...
Ultrasound (US) is a widely used as a low-cost alternative to computed tomography (CT) or magnetic resonance (MRI) and primarily for preliminary imaging. Since speckle intensity in US images is inherently stochastic, readers are often challenged in their ability to identify the pathological regions in a volume of a large number of images. This pape...
The classification of thyroid and non-thyroid regions in ultrasound images is of high clinical importance as changes in the thyroid shape and size act as indicators for thyroid diseases. We present a novel approach of features computation using the thyroid texture and classify them using two simple classification/clustering algorithms (linear discr...
The thyroid is one of the largest endocrine glands in the human body and is involved in protein synthesis as well as in controlling the human energy sources usage. It is very important to monitor the state of thyroid over time as most of the thyroid diseases like Graves’ disease, and thyroid cancer involves change in shape and size of the thyroid....
US guidance in combination with interventional MRI
Challenges and prospects of medical imaging and healthcare in Nepal in next decades
Prabal Poudel
Catheter Technologies, Otto-von-Guericke-University, Magdeburg, Germany, prabal.poudel@ovgu.de
1. Introduction
Medical Imaging is the process of visualizing interior body parts for non-invasive medical intervention and clinical analysis. The histor...
Thyroid segmentation in tracked 2D ultrasound (US) using active contours has a low segmentation accuracy mainly due to the fact that smaller structures cannot be efficiently recognized and segmented. To address this issue, we propose a new similarity indicator with the main objective to provide information to the active contour algorithm concerning...
The segmentation of the thyroid in ultrasound images is a field of active research. The thyroid is a gland of the endocrine system and regulates several body functions. Measuring the volume of the thyroid is regular practice of diagnosing pathological changes. In this work, we compare three approaches for semi-automatic thyroid segmentation in free...
Thyroid segmentation in tracked 2D ultrasound using active contours creating a 3D model has low segmentation accuracy mainly due to the fact that smaller structures cannot be efficiently recognized and segmented. To address that issue, we propose an improved method to by extending an active contour model in 2D to generate a 3D segmented thyroid vol...
In this paper, we propose a method to segment the thyroid from a set of 2D ultrasound images. We extended an active contour model in 2D to generate a 3D segmented thyroid volume. First, a preprocessing step is carried out to suppress the noise present in US data. Second, an active contour is used to segment the thyroid in each of the 2D images. Fin...
In this paper, we propose a method to segment the thyroid from a set of 2D ultrasound images. We extended an active contour model in 2D to generate a 3D segmented thyroid volume. First, a preprocessing step is carried out to suppress the noise present in US data. Second, an active contour is used to segment the thyroid in each of the 2D images. Fin...
Projects
Projects (3)
Use tracked 2D Ultrasound for 3D organ segmentation using machine learning and other approaches and merge it as a real-time and non-ionising imaging system for interventional procedures to 2D/3D X-Ray and in-room MRI.