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Medulloblastoma (MB) is the most common brain tumor in children. There are four distinct subtypes of MB, but patients with anaplastic/large cell have the worst prognosis. Since the morbidity is highly correlated with treatment for MB, the ability to distinguish aggressive (such as anaplastic/large cell) MB is crucial. We present a scheme that leverages quantitative image texture features (Haar, Haralick,...
Diagnosis of white matter damage by neonatal cranial ultrasound (CrUS) is subject to inter-observer variability and has a low sensitivity to detect late abnormal neurodevelopment in life. In the last decades there have been a significant effort reporting that statistical features of ultrasound images carry important information associated with changes of tissue microstructure. In this work we explored...
In this paper, we consider a novel low-complexity image processing-based approach to the detection of neonatal clonic seizures. Our approach is based on the extraction, from a video recording of a newborn, of an average luminosity signal representative of the body movements. Since clonic seizures are characterized by periodic movements of parts of the body (e.g., the limbs), by evaluating the periodicity...
Newborn swapping and abduction is a global problem and traditional approaches such as ID bracelets and footprinting do not provide the required level of security. This paper introduces the concept of using face recognition for identifying newborns and presents an automatic face recognition algorithm. The proposed multiresolution algorithm extracts Speeded up robust features and local binary patterns...
In this paper, we address the task of automatic digest generating of video data taken from kindergarten surveillance cameras. Our objective is extracting and merging video segments to recode children's daily life. In order to deal with mass video data efficiently, we jointly utilize location information and visual features to segment raw material videos. Our proposed method involves two steps. The...
In this paper, an automatic method is proposed to detect Retinopathy of prematurity (ROP) in premature infants. ROP is an ocular disease of low birth weight infants and it can cause blindness. It is essential that those caring for premature infants know who is at risk of ROP, when screening must begin and how often these infants need to be examined. So, ROP detection is necessary for both screening...
Machine based gender classification is one of the challenging problem to the computer science researchers. The effortless ability exhibited by a two year kid for the same needs immense computation power for the computing machines. Many people attempted this problem by using different psychological characteristics such as handwriting, speech recognition, query response etc. These computational intensive...
This paper describes the concept of segmentation and geometry restauration for two-dimensional scanner images of white roots from hydroponic cultures. The segmentation applies RGB to HSV colour spaces transform and takes into account high chroma and dark type discolourations of root tissue. To identify spatial root tree, all paths in its 2D projection graph are individually tracked, with some a priori...
The previous approach to vowel imitation learning between a caregiver and an infant (robot) has assumed that the robot can segment the caregiverpsilas utterance into its phoneme category, where the caregiver always imitates the robot utterance. However, in real situations, the caregiver does not always imitate the robot utterance, nor the robot does have the phoneme category (no segmentation capability)...
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