Výsledky vyhledávání - "VASUDEVA, AKHILA"

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Leveraging Clinically Relevant Biometric Constraints To Supervise A Deep Learning Model For The Accurate Caliper Placement To Obtain Sonographic Measurements Of The Fetal Brain

Autor: Shankar, Hari, Narayan, Adithya, Jain, Shefali, Singh, Divya, Vyas, Pooja, Hegde, Nivedita, Kar, Purbayan, Lad, Abhi, Thang, Jens, Atada, Jagruthi, Nguyen, Duy, Roopa, PS, Vasudeva, Akhila, Radhakrishnan, Prathima, Devalla, Sripad Krishna

Multiple studies have demonstrated that obtaining standardized fetal brain biometry from mid-trimester ultrasonography (USG) examination is key for the reliable assessment of fetal neurodevelopment and the screening of central nervous system (CNS) an

Externí odkaz: http://arxiv.org/abs/2203.14482

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Towards A Device-Independent Deep Learning Approach for the Automated Segmentation of Sonographic Fetal Brain Structures: A Multi-Center and Multi-Device Validation

Autor: Lad, Abhi, Narayan, Adithya, Shankar, Hari, Jain, Shefali, Vyas, Pooja Punjani, Singh, Divya, Hegde, Nivedita, Atada, Jagruthi, Thang, Jens, Nee, Saw Shier, Govindarajan, Arunkumar, PS, Roopa, Pai, Muralidhar V, Vasudeva, Akhila, Radhakrishnan, Prathima, Devalla, Sripad Krishna

Quality assessment of prenatal ultrasonography is essential for the screening of fetal central nervous system (CNS) anomalies. The interpretation of fetal brain structures is highly subjective, expertise-driven, and requires years of training experie

Externí odkaz: http://arxiv.org/abs/2202.13553

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