… as well as robust segmentation model for lungs and COVID-19 infected regions without …
for COVID-19 infection between predicted and annotated segmentation from radiologists of …

… of the infected areas inside the lungs more efficiently. The image of the detected lungs
achieved from the previous stage has to be clustered to segment the infected areas from the other …

… lung segmentation are not designed to deal with the specific problems present in Mtb-infected
lungs … In this work, we present an automatic pipeline able to segment lungs infected with …

… robust segmentation model for lungs and COVID-19 infected … of 0.956 for lungs and 0.761
for infection. We demonstrated … -19 segmentation and improves medical image analysis with …

… Parallel Partial Decoder: Several existing medical image segmentation networks segment
… Specifically, for an input CT image I, we first extract two sets of low-level features {fi,i = 1, 2} …

… In this sub-section, we focus on presenting a method that divides a CT image into COVID-19
lung infected from none infected regions. Extensive computer simulations show that the use …

… for COVID-19 lung infection segmentation and quantification … COVID-19 Lung Infection
segmentation and quantification using … for CT image segmentation using image enhancement is …

… , the percentage of infection in the whole lung. In the literature, … image analysis and has been
used in analyzing diffuse lung … to segment COVID-19 infection regions within lung fields on …

… Figure 12.4 shows a sample image of a lung infected with the coronavirus alongside a GT
image. Researchers have used criteria such as Dice coefficient, accuracy, precision, sensitivity…

… This paper proposes an automated segmentation method of infection and normal regions in
the lung … U-Net6 is commonly used in image segmentation. While the U-Net is effective for …