Google Inc.

Krishna Kumar Gadepalli

Vijnan Shastri

Krishnan Eswaran

Wendy Tobagus

Thierry Foucu

Jie Sun

Debargha Mukherjee

Rushabh Ashok Doshi

Huisheng Wang

Christophe Chaland

Martin Christian Stumpe

Lily Peng

Yun Liu

Timo Kohlberger

Charles Christian Krasic

Yang Xia

A method, system and machine for assisting a pathologist in identifying the presence of tumor cells in lymph node tissue is disclosed. The digital image of lymph node tissue at a first magnification (e.g., 40&#xd7;) is subdivided into a multitude of rectangular 'patches.' A likelihood of malignancy score is then determined for each of the patches. The score is obtained by analyzing pixel data from the patch (e.g., pixel data centered on and including the patch) using a computer system programmed as an ensemble of deep neural network pattern recognizers, each operating on different magnification levels of the patch. A representation or 'heatmap' of the slide is generated. Each of the patches is assigned a color or grayscale value in accordance with (1) the likelihood of malignancy score assigned to the patch by the combined outputs of the ensemble of deep neural network pattern recognizers and (2) a code which assigns distinct colors (or grayscale values) to different values of likelihood of malignancy scores assigned to the patches.

Method and system for assisting pathologist identification of tumor cells in magnified tissue images

A method includes separating, using a separation component, a plurality of input streams into a plurality of audio streams having different bitrates and a plurality of video streams having different bitrates; transcoding, using an audio transcoder, the plurality of audio streams into a plurality of transcoded audio streams having different transcode qualities; transcoding, using a video transcoder, the plurality of video streams into a plurality of transcoded video streams having different transcode qualities; segmenting, using a segmentation component, the plurality of audio streams into a plurality of equivalent audio segments based on identified segment boundaries associated with the plurality transcoded audio streams and the plurality of video streams into a plurality of equivalent video segments based on identified segment boundaries associated with the plurality of transcoded video streams; and joining, using a conjoining component, the plurality of equivalent audio segments and the plurality of video segments into a single stream.

Scalable, live transcoding with support for adaptive streaming and failover

A system and method for a live streaming platform that can redundantly process input streams in parallel ingestion pipelines is disclosed herein. Ingested input streams in the parallel pipelines can be segmented using a segmentation function that creates identical segments in each of the streams in the pipelines. If errors occur, or there are disruptions in one or more of the input streams or pipelines, the live streaming platform can ensure that segments are identifiable and different parts of the pipelines can join a main stream at different points in time without disruption.

A system and method provides transcoding a video in parallel by multiple transcoders based on a measure of video coding complexity (VCC). The system has a video pre-processing module, a master transcoder, a transcoding controller and multiple transcoders. The video pre-processing module transcodes a source video into an intermediate video. The master transcoder partitions the intermediate video into multiple transcoding units, where a transcoding unit identifies a portion of data of the intermediate video for transcoding. The master transcoder further generates a transcoding request for each transcoding unit. The transcoding controller distributes the transcoding units to the multiple transcoders, which transcode the data of the transcoding units in parallel into transcoded data.

Parallel video transcoding

Systems and methods for processing a live video stream are provided. An ingestion component receives segments of a live video stream in association with a request to process the live video stream. A control component generates an instruction graph for the live video stream based on predetermined criteria. The instruction graph defines a workflow for processing the live video stream, the workflow comprising a set of services for processing the segments. A transcoding component employs a subset of the services to process the segments based at least in part on the instruction graph and a distribution component then streams the segments to a device in response finishing process of the segments. With the live video processing system, segments of a video stream are processed and distributed as they are received. Thus segments of the video stream are processed and distributed prior to processing of the entire video stream.

Live streaming video processing

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Fremont, CA, United States of America

Krishna Kumar Gadepalli