GPU Accelerated Viscous-fluid Deformable Registration for Radiotherapy

In cancer treatment organ and tissue deformation betweenradiotherapy sessions represent a significant challenge to op-timal planning and delivery of radiation doses. Recent de-velopments in image guided radiotherapy has caused a soundrequest for more advanced approaches for image registrationto handle these deformations. Viscous-fluid registration isone such deformable registration method. A drawback withthis method has been that it has required computation timesthat were too long to make the approach clinically appli-cable. With recent advances in programmability of graph-ics hardware, complex user defined calculations can now beperformed on consumer graphics cards (GPUs). This pa-per demonstrates that the GPU can be used to drasticallyreduce the time needed to register two medical 3D imagesusing the viscous-fluid registration method. This facilitatesan increased incorporation of image registration in radio-therapy treatment of cancer patients, potentially leading tomore efficient treatment with less severe side effects

Significance of developmental meningeal lymphatic dysfunction in experimental post-traumatic injury

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Indigenous Protocol and Artificial Intelligence Position Paper

This position paper on Indigenous Protocol (IP) and Artificial Intelligence (AI) is a starting place for those who want to design and create AI from an ethical position that centers Indigenous concerns. Each Indigenous community will have its own particular approach to the questions we raise in what follows. What we have written here is not a substitute for establishing and maintaining relationships of reciprocal care and support with specific Indigenous communities. Rather, this document offers a range of ideas to take into consideration when entering into conversations which prioritize Indigenous perspectives in the development of artificial intelligence. It captures multiple layers of a discussion that happened over 20 months, across 20 time zones, during two workshops, and between Indigenous people (and a few non-Indigenous folks) from diverse communities in Aotearoa, Australia, North America, and the Pacific. Indigenous ways of knowing are rooted in distinct, sovereign territories across the planet. These extremely diverse landscapes and histories have influenced different communities and their discrete cultural protocols over time. A single ‘Indigenous perspective’ does not exist, as epistemologies are motivated and shaped by the grounding of specific communities in particular territories. Historically, scholarly traditions that homogenize diverse Indigenous cultural practices have resulted in ontological and epistemological violence, and a flattening of the rich texture and variability of Indigenous thought. Our aim is to articulate a multiplicity of Indigenous knowledge systems and technological practices that can and should be brought to bear on the ‘question of AI.’ To that end, rather than being a unified statement this position paper is a collection of heterogeneous texts that range from design guidelines to scholarly essays to artworks to descriptions of technology prototypes to poetry. We feel such a somewhat multivocal and unruly format more accurately reflects the fact that this conversation is very much in an incipient stage as well as keeps the reader aware of the range of viewpoints expressed in the workshops

Kaʻina Hana ʻŌiwi a me ka Waihona ʻIke Hakuhia Pepa Kūlana

He wahi hoʻomaka kēia pepa kuana no ke Kaʻina Hana ʻŌiwi (KHʻO) a me ka Waihona ʻike Hakuhia (WʻIH) no ka poʻe e ake nei e haku a hana he WʻIK mai ke kuanaʻike kūpono e hoʻokele ʻia nei e ka manaʻo ʻŌiwi. He kiʻina hana ko kēlā a me kēia kaiāulu ʻŌiwi i nā nīnau a mākou e ui aʻe ai. ʻAʻole kēia mea a mākou i kākau ai he pani i ke kūkulu a mālama ʻana i ka pilina kākoʻo kekahi i kekahi me kekahi mau kaiāulu ʻŌiwi. Eia naʻe, hāpai aʻe kēia palapala i kekahi mau manaʻo e noʻonoʻo ai ke komo i kēia mau kamaʻilio ʻana ʻo ka hoʻomaka koho ʻana i ke kuanaʻike ʻŌiwi i ka haku ʻana he waihona ʻike hakuhia. He hoʻāʻo kēia wahi pepa kūlana e hōʻiliʻili i nā ʻano kamaʻilio like ʻole no 20 mahina, no 20 kāʻei hola, no ʻelua hālāwai hoʻonaʻauao, a ma waena hoʻi o kekahi mau poʻe ʻŌiwi (a ʻŌiwi ʻole hoʻi) no nā kaiāulu like ʻole i Aotearoa, Nū Hōlani, ʻAmelika ʻĀkau a me ka Pākīpika. ʻO ke kia nō naʻe, ʻaʻole ʻo ka hoʻolōkahi ʻana he leo. Paʻa nō ka ʻike ʻŌiwi i kekahi mau ʻāina a aupuni kikoʻī a puni ka honua. Hoʻohuli aku kēia mau ʻāina a mōʻaukala like ʻole i nā kaiāulu ʻokoʻa a me ko lākou mau kaʻina hana ʻŌiwi i ke au o ka manawa. ʻAʻohe “kuanaʻike ʻŌiwi hoʻokahi”, a hoʻomau a haku ʻia nā kālaikuhiʻike e ka hoʻokumu ʻana o kekahi mau kaiāulu kikoʻī i loko o kahi mau ʻāina. Ma mua, he hopena ulūlu o ke kālaikuhiʻike a kālaikuhikanaka ko ka loina naʻauao i hoʻāʻo e naʻi a hoʻohilimia i ka loina ʻŌiwi, a hoʻohāiki ʻia ke ʻano o ka manaʻo a kuanaʻike ʻŌiwi. ʻO ko mākou pahuhopu ke kālele ʻana i nā ʻōnaehana ʻike ʻŌiwi like ʻole a me ke ʻano o ka ʻenehana e hāpai i ka nīnau ʻo ka WʻIH. Ma muli o ia palena, a ma kahi o ka hoʻokuʻikuʻi ʻana he manaʻo lōkahi, he hōʻiliʻili kēia pepa kūlana o kēlā ʻano kēia ʻano o ka moʻokalaleo: ʻo nā manaʻo hoʻokele hakulau ʻoe,, ʻo ka ʻatikala akeakamai ʻoe, ʻo ka wehewehena o ka mana ʻenehana mua ʻoe , a ʻo ka poema ʻoe. I ko mākou manaʻo, he ʻolokeʻa kūpono maoli nā leo a kuanaʻike ʻokoʻa i ka ʻoiaʻiʻo he pae kinohi maoli nō kēia kamaʻilio ʻana, a he hōʻike i ka mea heluhelu no nā kuanaʻike i kupu mai i loko o nā hālāwai hoʻonaʻauao

A Framework for Equitable Design in Extended Reality Cultural Heritage Exhibitions

M.S

Kilo Hōkū

Kilo Hōkū is a virtual reality simulation for non-instrument open ocean Hawaiian navigation. The simulation re-creates, within a virtual environment, the experience of utilizing non-instrument navigation techniques on a wa’a kaulua, a Hawaiian double-hulled sailing canoe. It is intended to help both learners and instructors of Modern Hawaiian wayfinding by allowing the user to be immersed in an open ocean setting

Virtual Reality and Visualization in Research and Cultural Preservation

Visualization as a field can be defined as the process of turning data into interactive images to provide insight or knowledge to a user. New innovations in virtual reality hardware open up new opportunities in the field of visualization, rather than merely for entertainment. My research portfolio and poster highlight two visualization projects that I have created that utilize current virtual reality hardware, the HTC Vive and the University of Hawaiʻi at Mānoa’s Laboratory of Advanced Visualization and Applications (LAVA) Destiny-class CyberCANOE. The At-Risk Artifact Visualization System will allow users to view and study 3D models of archaeological artifacts and sites that are considered “at-risk” within the cyberCANOE. “At-risk” in this case is defined as: an archaeological artifact or site in danger of destruction by either human or environmental influences. Kilo Hōkū, optimized for the HTC Vive, is an immersive virtual reality simulation to aid in the visualization and education of Hawaiian star navigation practices. The goal of this portfolio is to demonstrate the possibilities virtual reality and visualization have for the field of cultural preservation

Acceleration and validation of optical flow based deformable registration for image-guided radiotherapy

International audienceMaterials and methods: Two registration methods based on optical flow estimation have been programmed to run on a graphics programming unit (GPU). One of these methods by Horn & Schunck is tested on a 4DCT thorax data set with 10 phases and 41 landmarks identified per phase. The other method by Cornelius & Kanade is tested on a series of six 3D cone beam CT (CBCT) data sets and a conventional planning CT data set from a head and neck cancer patient. In each of these data sets 6 landmark points have been identified on the cervical vertebrae and the base of skull. Both CBCT to CBCT and CBCT to CT registration is performed.Results: For the 4DCT registration average landmark error was reduced by deformable registration from 3.5 ± 2.0 mm to 1.1 ± 0.6 mm. For CBCT to CBCT registration the average bone landmark error was 1.8 ± 1.0 mm after rigid registration and 1.6 ± 0.8 mm after deformable registration. For CBCT to CT registration errors were 2.2 ± 0.6 mm and 1.8 ± 0.6 mm for rigid and deformable registration respectively. Using GPU hardware the Horn & Schunck method was accelerated by a factor of 48. The 4DCT registration can be performed in 37 seconds. The head and neck cancer patient registration takes 64 seconds.Discussion: Compared to image slice thickness, which limits accuracy of landmark point determination, we consider the landmark point accuracy of the registration acceptable. The points identified in the CBCT images do not give a full impression of the result of doing deformable registration as opposed to rigid registration. A larger validation study is being planned in which soft tissue landmarks will facilitate tracking the deformableregistration. The acceleration obtained using GPU hardware means that registration can be done online for CBCT