Techniques and challenges of image segmentation: A review
Y Yu, C Wang, Q Fu, R Kou, F Huang, B Yang, T Yang… - Electronics, 2023 - mdpi.com
Image segmentation, which has become a research hotspot in the field of image processing
and computer vision, refers to the process of dividing an image into meaningful and non …
and computer vision, refers to the process of dividing an image into meaningful and non …
Demystifying supervised learning in healthcare 4.0: A new reality of transforming diagnostic medicine
The global healthcare sector continues to grow rapidly and is reflected as one of the fastest-
growing sectors in the fourth industrial revolution (4.0). The majority of the healthcare …
growing sectors in the fourth industrial revolution (4.0). The majority of the healthcare …
Bone fracture detection using deep supervised learning from radiological images: A paradigm shift
Bone diseases are common and can result in various musculoskeletal conditions (MC). An
estimated 1.71 billion patients suffer from musculoskeletal problems worldwide. Apart from …
estimated 1.71 billion patients suffer from musculoskeletal problems worldwide. Apart from …
Detection of lung cancer in CT scans using grey wolf optimization algorithm and recurrent neural network
Purpose For radiologists, identifying and assessing thelung nodules of cancerous form from
CT scans is a difficult and laborious task. As a result, early lung growing prediction is …
CT scans is a difficult and laborious task. As a result, early lung growing prediction is …
[HTML][HTML] Deep learning models for tuberculosis detection and infected region visualization in chest X-ray images
Objective Tuberculosis (TB) is among the most frequent causes of infectious-disease-related
mortality. Despite being treatable by antibiotics, tuberculosis often goes misdiagnosed and …
mortality. Despite being treatable by antibiotics, tuberculosis often goes misdiagnosed and …
Integrative approaches in acute ischemic stroke: from symptom recognition to future innovations
VM Saceleanu, C Toader, H Ples… - Biomedicines, 2023 - mdpi.com
Among the high prevalence of cerebrovascular diseases nowadays, acute ischemic stroke
stands out, representing a significant worldwide health issue with important socio-economic …
stands out, representing a significant worldwide health issue with important socio-economic …
Assessing inter-annotator agreement for medical image segmentation
Artificial Intelligence (AI)-based medical computer vision algorithm training and evaluations
depend on annotations and labeling. However, variability between expert annotators …
depend on annotations and labeling. However, variability between expert annotators …
Attention-based UNet deep learning model for plaque segmentation in carotid ultrasound for stroke risk stratification: an artificial intelligence paradigm
Stroke and cardiovascular diseases (CVD) significantly affect the world population. The
early detection of such events may prevent the burden of death and costly surgery …
early detection of such events may prevent the burden of death and costly surgery …
A multi-objective segmentation method for chest X-rays based on collaborative learning from multiple partially annotated datasets
Accurate segmentation of multiple targets, such as ribs, clavicles, heart, and lung fields, from
chest X-ray images is crucial for diagnosing various lung diseases. Currently, mainstream …
chest X-ray images is crucial for diagnosing various lung diseases. Currently, mainstream …
BMRI-NET: A deep stacked ensemble model for multi-class brain tumor classification from MRI images
S Asif, M Zhao, X Chen, Y Zhu - Interdisciplinary Sciences: Computational …, 2023 - Springer
Brain tumors are one of the most dangerous health problems for adults and children in many
countries. Any failure in the diagnosis of brain tumors may lead to shortening of human life …
countries. Any failure in the diagnosis of brain tumors may lead to shortening of human life …