Zobrazeno 1 - 10
of 9 342
pro vyhledávání: '"Linda, G"'
Autor:
Bigverdi, Mahtab, Luo, Zelun, Hsieh, Cheng-Yu, Shen, Ethan, Chen, Dongping, Shapiro, Linda G., Krishna, Ranjay
Multimodal language models (MLMs) still face challenges in fundamental visual perception tasks where specialized models excel. Tasks requiring reasoning about 3D structures benefit from depth estimation, and reasoning about 2D object instances benefi
Externí odkaz:
http://arxiv.org/abs/2412.03548
Autor:
Liu, Zixuan, Xu, Hanwen, Woicik, Addie, Shapiro, Linda G., Blazes, Marian, Wu, Yue, Steffen, Verena, Cukras, Catherine, Lee, Cecilia S., Zhang, Miao, Lee, Aaron Y., Wang, Sheng
We present OCTCube-M, a 3D OCT-based multi-modal foundation model for jointly analyzing OCT and en face images. OCTCube-M first developed OCTCube, a 3D foundation model pre-trained on 26,685 3D OCT volumes encompassing 1.62 million 2D OCT images. It
Externí odkaz:
http://arxiv.org/abs/2408.11227
Autor:
Han, Jiashu, Liu, Kunzan, Isaacson, Keith B., Monakhova, Kristina, Griffith, Linda G., You, Sixian
Three-dimensional (3D) subcellular imaging is essential for biomedical research, but the diffraction limit of optical microscopy compromises axial resolution, hindering accurate 3D structural analysis. This challenge is particularly pronounced in lab
Externí odkaz:
http://arxiv.org/abs/2406.06337
Autor:
Liu, Kunzan, Cao, Honghao, Shashaty, Kasey, Yu, Li-Yu, Spitz, Sarah, Pramotton, Francesca Michela, Wan, Zhengpeng, Kan, Ellen L., Tevonian, Erin N., Levy, Manuel, Lendaro, Eva, Kamm, Roger D., Griffith, Linda G., Wang, Fan, Qiu, Tong, You, Sixian
Label-free imaging through two-photon autofluorescence (2PAF) of NAD(P)H allows for non-destructive and high-resolution visualization of cellular activities in living systems. However, its application to thick tissues and organoids has been restricte
Externí odkaz:
http://arxiv.org/abs/2404.11901
Accurate cancer diagnosis remains a critical challenge in digital pathology, largely due to the gigapixel size and complex spatial relationships present in whole slide images. Traditional multiple instance learning (MIL) methods often struggle with t
Externí odkaz:
http://arxiv.org/abs/2404.10894
Autor:
Marathe, Kalyani, Bigverdi, Mahtab, Khan, Nishat, Kundu, Tuhin, Howe, Patrick, S, Sharan Ranjit, Bhattad, Anand, Kembhavi, Aniruddha, Shapiro, Linda G., Krishna, Ranjay
Dense pixel-specific representation learning at scale has been bottlenecked due to the unavailability of large-scale multi-view datasets. Current methods for building effective pretraining datasets heavily rely on annotated 3D meshes, point clouds, a
Externí odkaz:
http://arxiv.org/abs/2306.15128
Autor:
Andreas Nygaard, Linda G. Zachariassen, Kathrine S. Larsen, Anders S. Kristensen, Claus J. Loland
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-14 (2024)
Abstract The serotonin transporter (SERT), responsible for the reuptake of released serotonin, serves as a major target for antidepressants and psychostimulants. Nevertheless, refining the mechanistic models for SERT remains challenging. Here, we exp
Externí odkaz:
https://doaj.org/article/a5f88a26a4c94938bb5c189b7d6b8b3b
Publikováno v:
Frontiers in Reproductive Health, Vol 6 (2024)
Externí odkaz:
https://doaj.org/article/ce4e948017e54a80ba5ecd096de0539d