Pramana Inc.

Microsoft Technology Licensing, LLC

Prateek Jain

Prasanth Perugupalli

Raghubansh Bahadur Gupta

Jaya Jain

Durgaprasad Dodle

Shilpa G Krishna

Sumit Gulwani

Manish Shiralkar

Oleksandr Polozov

Priyanka Golchha

Jithin Prems

Asa Rubin

Ramarathnam R Venkatesan

Jonathan Alexander Lee

Daniel Adam Perelman

Parveen Shaik Gangirevula

Saswat Padhi

Rohan Prateek

Anurag Mishra

Kartik Gupta

Darshatkumar Anandji Shah

Ayush Choure

Lekshmi Menon

Navya Yarrabelly

Mohammad Luqman

Amar Budhiraja

Shivangi Dhakad

Juhi Dua

Gaurush Hiranandani

Ganesh Ramamoorthy

Dipankar Das

Bharathwaj Raghunathan

Tasin Ahmed

Vaibhav Singh

Abhishek Mohta

Himansh Mulchandani

Rachna Shukla

Suhash Gerald

Deepak Anand

Ashwin Kalyan Vijayakumar

A method for visualization of digitized slides is disclosed. The method comprises retrieving, by one or more computer processors, a digitized slide, determining, by the one or more computer processors, one or more visualization components of the digitized slide, generating, by the one or more computer processors, a virtual slide corresponding to the digitized slide based on the one or more visualization components, and displaying, by the one or more computer processors, a visualization of the virtual slide.

System and method for visualization of digitized slides

An apparatus for identifying regions of interest during slide digitization is disclosed. The apparatus includes at least processor and a memory communicatively connected to the processor. The memory contains instructions configuring the processor to receive a user dataset associated with at least a pathology slide. The memory contains instructions configuring the processor to identify one or more regions of interest within at least a pathology slide as a function of the user dataset. The memory contains instructions configuring the processor to identify at least one scan parameter as a function of the one or more regions of interest. The memory contains instructions configuring the processor to generate a digitized slide by scanning the at least a pathology slide as a function the at least one scan parameter.

Apparatus and method for identifying regions of interest during slide digitization

The present disclosure describes an exemplary system and method for the digitization of tissue slides based on associations among serial sections. The system includes at least a computing device, wherein the computing device includes a memory and processor communicatively connected to one another, and a scanner, configured to scan a slide and send a digitized image of the slide to the computing device. A method for the digitization of tissue slides based on associations among serial sections may include receiving a candidate tissue map associated with a candidate tissue section, receiving a reference tissue map associated with a reference tissue section, aligning the candidate tissue map to the reference tissue map, comparing the aligned candidate tissue map to the reference tissue map, and generating a regenerated candidate tissue map as a function of the reference tissue map.

Systems and methods for digitization of tissue slides based on associations among serial sections

A system for color gamut normalization for pathology slides, the system including at least computing device, wherein the computing device is configured to receive a whole slide image, generate a plurality of segments associated with the whole slide image as a function of one or more biological tissue type variabilities, apply a segment-specific transformation to each segment of the plurality of segments, create a user interface data structure, wherein the user interface data structure includes the plurality of segments and display the plurality of segments through a graphical user interface as a function of the user interface data structure.

System and methods for color gamut normalization for pathology slides

An apparatus for visualization of digitized glass slides belonging to a patient case having a processor and a memory communicatively connected to the processor, the memory containing instructions configuring the processor to receive an image data set having a plurality of images of one or more specimen and metadata of the plurality of images of the one or more specimen, identify one or more constituent virtualization components for each image of the plurality of images within image data set, determine a relationship between the one or more constituent visualization components as a function of the image data set, construct a plurality of virtual images as a function of the image data set and the relationship between the one or more virtual constituent components, wherein each of plurality of the images includes at least one virtual constituent component generate a consolidated virtual image as a function of the plurality of virtual images and display the consolidated virtual image.

Apparatus and method for visualization of digitized glass slides belonging to a patient case

Aspects of present disclosure relate to slide imaging. An exemplary system for imaging a slide includes at least an optical system, including an optical sensor; a slide port configured to hold a slide; and a first computing device configured to: capture, using the at least an optical system, a plurality of images of the slide, including a first image; automatically select an algorithm to apply to the first image; identify a control command as a function of the first image; and capture, using the at least an optical system, a second image of the plurality of images as a function of the control command.

System and methods for slide imaging

An apparatus and method for inline scanned image enrichment is provided. The apparatus includes a computing device configured to receive a plurality of subject data, generate a candidate set to model the scan focal points from, digitally capture the slide using the identified focal points through machine-learning processes, processing the captured image to optimize its viewability, and storing the captured image in an accessible repository.

Method and an apparatus for inline image scan enrichment

A system for color gamut normalization for pathology slide is disclosed. The system includes at least a computing device, wherein the computing device is configured to generate a plurality of segmentations of a whole slide image, wherein the whole slide image includes a plurality of biological tissue type variabilities. The computing device is configured to apply a segment-specific transformation to an individual segment in a first region. The computing device is configured to apply the segment-specific transformation to an individual segment in a second region. The computing device is configured to retrieve a plurality of discrete magnification levels from a user. The computing device is configured to choose as a first magnification level from the plurality of discrete magnification levels, and the computing device is configured to store the plurality of segmentations in a cache.

Systems and methods for entity recommendation can make use of rich data by allowing the items to be recommended and the recipients of the recommendation (e.g., users) to be modeled as 'complex entities' composed of one or more static sub-entities and/or a dynamic component, and by utilizing information about multiple relationships between the sub-entities as reflected in bipartite graphs. Generating recommendations from such information may involve creating vector representations of the sub-entities based on the bipartite graphs (e.g., using graph-based convolutional networks), and combining these vector representations into representations of the items and users (or other recipients) to be fed into a classifier model.

Multiple-entity-based recommendation system

A computing device includes a storage machine holding instructions executable by a logic machine to generate multi-string clusters, each containing alphanumeric strings of a dataset. Further multi-string clusters are generated via iterative performance of a combination operation in which a hierarchically-superior cluster is generated from a set of multi-string clusters. The combination operation includes, for candidate pairs of multi-string clusters, generating syntactic profiles describing an alphanumeric string from each multi-string cluster of the candidate pair. For each of the candidate pairs, a cost factor is determined for at least one of its syntactic profiles. Based on the cost factors determined for the syntactic profiles, one of the candidate pairs is selected. The multi-string clusters from the selected candidate pair are combined to generate the hierarchically-superior cluster including all of the alphanumeric strings from the selected candidate pair of multi-string clusters.

Syntactic profiling of alphanumeric strings

Message recommendation system

Systems, methods, and computer-executable instructions for guiding program synthesis includes receiving a specification that includes an input and output example. Programs are synthesized that meet the specification. During synthesizing each of the programs includes branching decisions. Each branching decision includes a plurality of paths. Synthesizing the programs comprises includes selecting a first score model, for a first branching decision. Each of the programs is scored using the first score model. The paths of the first branching decision are pared based on the score. One the paths is selected. A synthesized program that meets the specification is returned. The synthesized program includes the one of the paths.

Neural-guided deductive search for program synthesis

Systems, methods, and computer-executable instructions for secure data analysis using encrypted data. An encryption key and a decryption key are created. The security of encryption using the encryption key and the decryption key are based upon factoring. A computation key is created based upon the encryption key. Data is encrypted using the encryption key. The encrypted data and the computation key are provided to a remote system. The remote system is requested to perform data analysis on the encrypted data. An encrypted result of the data analysis is received from the remote system. The encrypted result of the data analysis is decrypted with the decryption key.

Homomorphic factorization encryption

Systems, methods, and computer-executable instructions for homomorphic data analysis. Encrypted data is received, from a remote system, that has been encrypted with an encryption key. A number of iterations to iterate over the encrypted data is determined. A model is iterated over by the number of iterations to create an intermediate model. Each iteration updates the model, and the model and the intermediate model encrypted with the encryption key. The intermediate model is provided to the remote system. An updated model based upon the intermediate model is received from the remote system. The updated model is iterated over until a predetermined precision is reached to create a final model. The final model is provided to the remote system. The final model is encrypted with the encryption key.

Homomorphic data analysis

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Bengaluru, India

Prateek Jain