Semantic image segmentation is the process of labeling each pixel of an image with its corresponding class. An encoder-decoder based approach, like U-Net and its variants, is a popular strategy for solving medical image segmentation tasks. To improve the performance of U-Net on various segmentation tasks, we propose a novel architecture called DoubleU-Net, Architecture DoubleUNet […]

Deep learning models, such as neural networks, have become increasingly popular in recent years due to their ability to learn and make predictions from large amounts of data. However, one of the major challenges with these models is that they can be difficult to understand and interpret. This is known as the “black box” problem, […]

Radiation therapy (also known as Radiotherapy) is a procedure of cancer treatment that uses high-energy radiation to kill cancer cells. Artificial Intelligence (AI) is revolutionizing the field of cancer treatment, including the use of radiation therapy. Radiation therapy is a common treatment option for cancer that uses high-energy rays to target and kill cancer cells. […]

Introduction Recently, there has been a significant shift in the field of natural language processing (NLP), towards the use of transformers. Some examples of specific NLP tasks that Transformers have been used for include Language Translation, Text Generation, Text Summarization, Sentiment Analysis, Dialogue Generation and language modelling.  Transformers, which were first introduced in a 2017 […]

Gastrointestinal (GI) cancers are among the most common cancers worldwide. In particular, colorectal cancer is the most lethal in terms of the number of incidences and mortality (third most common cause of cancer and the second most common cause of cancer-related deaths). Colonoscopy is the gold standard for screening patients for colorectal cancer. During the […]

Introduction: ResUNet++ is built upon the Deep Residual U-Net (ResUNet) and UNet. However, ResUNet++ goes further, embedding: Residual Blocks: Ensuring information propagation across layers. Squeeze and Excitation Blocks: Recalibrating feature responses for better representation. ASPP (Atrous Spatial Pyramidal Pooling): Enlarging filter’s field-of-view to capture broader contexts. Attention Blocks: Enhancing the relevance of feature maps in […]