161 citations · 173 across the 12 of their papers we have counts for
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GCS-M3VLT: Guided Context Self-Attention based Multi-modal Medical Vision Language Transformer for Retinal Image Captioning
Teja Krishna Cherukuri, Nagur Shareef Shaik, Jyostna Devi Bodapati +1
Retinal image analysis is crucial for diagnosing and treating eye diseases, yet generating accurate medical reports from images remains challenging due to variability in image qual…
Multi-modal Imaging Genomics Transformer: Attentive Integration of Imaging with Genomic Biomarkers for Schizophrenia Classification
Nagur Shareef Shaik, Teja Krishna Cherukuri, Vince D. Calhoun +1
Schizophrenia (SZ) is a severe brain disorder marked by diverse cognitive impairments, abnormalities in brain structure, function, and genetic factors. Its complex symptoms and ove…
M3T: Multi-Modal Medical Transformer to bridge Clinical Context with Visual Insights for Retinal Image Medical Description Generation
Nagur Shareef Shaik, Teja Krishna Cherukuri, Dong Hye Ye
Automated retinal image medical description generation is crucial for streamlining medical diagnosis and treatment planning. Existing challenges include the reliance on learned ret…
Guided Context Gating: Learning to leverage salient lesions in retinal fundus images
Teja Krishna Cherukuri, Nagur Shareef Shaik, Dong Hye Ye
Effectively representing medical images, especially retinal images, presents a considerable challenge due to variations in appearance, size, and contextual information of pathologi…
Spatial Sequence Attention Network for Schizophrenia Classification from Structural Brain MR Images
Nagur Shareef Shaik, Teja Krishna Cherukuri, Vince Calhoun +1
Schizophrenia is a debilitating, chronic mental disorder that significantly impacts an individual's cognitive abilities, behavior, and social interactions. It is characterized by s…