Pulmonary Embolism (PE) has diverse manifestations with different etiologies such as venous thromboembolism, septic embolism, and paradoxical embolism. In this study, a novel attention-based multi-task model is proposed for PE segmentation and detection from Computed Tomography Pulmonary Angiography (CTPA) images. A Y-Net architecture is used to implement this model, which facilitates segmentation and classification jointly, improving performance and efficiency. It is leveraged with Multi Head Attention (MHA), which allows the model to focus on important regions of the image while suppressing irrelevant information, improving the accuracy of the segmentation and detection tasks. The proposed PE-YNet model is tested with two public datasets, achieving a maximum mean detection and segmentation accuracy of 99.89% and 99.83%, respectively, on the CAD-PE challenge dataset. Similarly, it also achieves a detection accuracy of 99.75% and a segmentation accuracy of 99.81% on the FUMPE dataset. Additionally, sensitivity analysis also shows a high sensitivity of 0.9885 for the localization error ɛ = 0 for the CAD-PE dataset, demonstrating the model's robustness against false predictions compared to state-of-the-art models. Further, this model also exhibits lower inference time, size, and memory usage compared to representative models. An automated PE-YNet tool can assist physicians with PE diagnosis, treatment, and prognosis monitoring in the clinical management of CoVID-19.
Over recent years, keratin has gained great popularity due to its exceptional biocompatible and biodegradable nature. It has shown promising results in various industries like poultry, textile, agriculture, cosmetics, and pharmaceutical. Keratin is a multipurpose biopolymer that has been used in the production of fibrous composites, and with necessary modifications, it can be developed into gels, films, nanoparticles, and microparticles. Its stability against enzymatic degradation and unique biocompatibility has found their way into biomedical applications and regenerative medicine. This review discusses the structure of keratin, its classification and its properties. It also covers various methods by which keratin is extracted like chemical hydrolysis, enzymatic and microbial treatment, dissolution in ionic liquids, microwave irradiation, steam explosion technique, and thermal hydrolysis or superheated process. Special emphasis is placed on its utilisation in the form of hydrogels, films, fibres, sponges, and scaffolds in various biotechnological and industrial sectors. The present review can be noteworthy for the researchers working on natural protein and related usage.