255 citations · 1.2k across the 18 of their papers we have counts for
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BT-Unet: A self-supervised learning framework for biomedical image segmentation using Barlow Twins with U-Net models
Narinder Singh Punn, Sonali Agarwal
Deep learning has brought the most profound contribution towards biomedical image segmentation to automate the process of delineation in medical imaging. To accomplish such task, t…
RCA-IUnet: A residual cross-spatial attention guided inception U-Net model for tumor segmentation in breast ultrasound imaging
Narinder Singh Punn, Sonali Agarwal
The advancements in deep learning technologies have produced immense contributions to biomedical image analysis applications. With breast cancer being the common deadliest disease…
MAG-Net: Multi-task attention guided network for brain tumor segmentation and classification
Sachin Gupta, Narinder Singh Punn, Sanjay Kumar Sonbhadra +1
Brain tumor is the most common and deadliest disease that can be found in all age groups. Generally, MRI modality is adopted for identifying and diagnosing tumors by the radiologis…
Modality specific U-Net variants for biomedical image segmentation: A survey
Narinder Singh Punn, Sonali Agarwal
With the advent of advancements in deep learning approaches, such as deep convolution neural network, residual neural network, adversarial network; U-Net architectures are most wid…
CHS-Net: A Deep learning approach for hierarchical segmentation of COVID-19 infected CT images
Narinder Singh Punn, Sonali Agarwal
The pandemic of novel SARS-CoV-2 also known as COVID-19 has been spreading worldwide, causing rampant loss of lives. Medical imaging such as CT, X-ray, etc., plays a significant ro…
Automated diagnosis of COVID-19 with limited posteroanterior chest X-ray images using fine-tuned deep neural networks
Narinder Singh Punn, Sonali Agarwal
The novel coronavirus 2019 (COVID-19) is a respiratory syndrome that resembles pneumonia. The current diagnostic procedure of COVID-19 follows reverse-transcriptase polymerase chai…