{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,21]],"date-time":"2026-02-21T10:24:21Z","timestamp":1771669461400,"version":"3.50.1"},"reference-count":32,"publisher":"MDPI AG","issue":"20","license":[{"start":{"date-parts":[[2021,10,19]],"date-time":"2021-10-19T00:00:00Z","timestamp":1634601600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Diabetic retinopathy (DR) is a diabetes disorder that disturbs human vision. It starts due to the damage in the light-sensitive tissues of blood vessels at the retina. In the beginning, DR may show no symptoms or only slight vision issues, but in the long run, it could be a permanent source of impaired vision, simply known as blindness in the advanced as well as in developing nations. This could be prevented if DR is identified early enough, but it can be challenging as we know the disease frequently shows rare signs until it is too late to deliver an effective cure. In our work, we recommend a framework for severity grading and early DR detection through hybrid deep learning Inception-ResNet architecture with smart data preprocessing. Our proposed method is composed of three steps. Firstly, the retinal images are preprocessed with the help of augmentation and intensity normalization. Secondly, the preprocessed images are given to the hybrid Inception-ResNet architecture to extract the vector image features for the categorization of different stages. Lastly, to identify DR and decide its stage (e.g., mild DR, moderate DR, severe DR, or proliferative DR), a classification step is used. The studies and trials have to reveal suitable outcomes when equated with some other previously deployed approaches. However, there are specific constraints in our study that are also discussed and we suggest methods to enhance further research in this field.<\/jats:p>","DOI":"10.3390\/s21206933","type":"journal-article","created":{"date-parts":[[2021,10,20]],"date-time":"2021-10-20T21:31:26Z","timestamp":1634765486000},"page":"6933","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":24,"title":["Severity Grading and Early Retinopathy Lesion Detection through Hybrid Inception-ResNet Architecture"],"prefix":"10.3390","volume":"21","author":[{"given":"Sana","family":"Yasin","sequence":"first","affiliation":[{"name":"Faculty of Computing, University of Okara, Okara 56141, Pakistan"}]},{"given":"Nasrullah","family":"Iqbal","sequence":"additional","affiliation":[{"name":"Faculty of Computing, University of Okara, Okara 56141, Pakistan"}]},{"given":"Tariq","family":"Ali","sequence":"additional","affiliation":[{"name":"Department of Computer Science, COMSATS University Islamabad (CUI), Sahiwal Campus, Sahiwal 57000, Pakistan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9576-5249","authenticated-orcid":false,"given":"Umar","family":"Draz","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of Sahiwal, Sahiwal 57000, Pakistan"},{"name":"Computer Science Department, CUI, Lahore Campus, Lahore 54000, Pakistan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7111-8810","authenticated-orcid":false,"given":"Ali","family":"Alqahtani","sequence":"additional","affiliation":[{"name":"College of Computer Science and Information Systems, Najran University, Najran 11001, Saudi Arabia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4161-6875","authenticated-orcid":false,"given":"Muhammad","family":"Irfan","sequence":"additional","affiliation":[{"name":"Electrical Engineering Department, College of Engineering, Najran University Saudi Arabia, Najran 61441, Saudi Arabia"}]},{"given":"Abdul","family":"Rehman","sequence":"additional","affiliation":[{"name":"IT Department, Superior University, Lahore 120000, Pakistan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0546-7083","authenticated-orcid":false,"given":"Adam","family":"Glowacz","sequence":"additional","affiliation":[{"name":"Department of Automatic Control and Robotics, Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering, AGH University of Science and Technology, al. A. Mickiewicza 30, 30-059 Krakow, Poland"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8664-8953","authenticated-orcid":false,"given":"Samar","family":"Alqhtani","sequence":"additional","affiliation":[{"name":"College of Computer Science and Information Systems, Najran University, Najran 11001, Saudi Arabia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8160-007X","authenticated-orcid":false,"given":"Klaudia","family":"Proniewska","sequence":"additional","affiliation":[{"name":"Department of Bioinformatics and Telemedicine, Jagiellonian University Medical College, Anny 12, 31-008 Krakow, Poland"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7475-3724","authenticated-orcid":false,"given":"Frantisek","family":"Brumercik","sequence":"additional","affiliation":[{"name":"Department of Design and Machine Elements, Faculty of Mechanical Engineering, University of Zilina, Univerzitna 1, 010 26 Zilina, Slovakia"}]},{"given":"Lukasz","family":"Wzorek","sequence":"additional","affiliation":[{"name":"Wzorek. Systems, ul. Kapelanka 10\/18, 30-347 Krakow, Poland"}]}],"member":"1968","published-online":{"date-parts":[[2021,10,19]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Khojasteh, P., Aliahmad, B., and Kumar, D.K. (2018). Fundus images analysis using deep features for detection of exudates, hemorrhages and microaneurysms. BMC Ophthalmol., 18.","DOI":"10.1186\/s12886-018-0954-4"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"200","DOI":"10.1016\/j.procs.2016.07.014","article-title":"Convolutional neural networks for diabetic retinopathy","volume":"90","author":"Pratt","year":"2016","journal-title":"Procedia Comput. Sci."},{"key":"ref_3","first-page":"25","article-title":"Handling imbalanced datasets: A review","volume":"30","author":"Kotsiantis","year":"2006","journal-title":"GESTS Int. Trans. Comput. Sci. 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