SOURCES SOUGHT
R -- Novel Classification Method Development for Biomedical Images
- Notice Date
- 8/12/2015
- Notice Type
- Sources Sought
- NAICS
- 541712
— Research and Development in the Physical, Engineering, and Life Sciences (except Biotechnology)
- Contracting Office
- Department of Health and Human Services, National Institutes of Health, National Library of Medicine, 6707 Democracy Blvd., Suite 105, Bethesda, Maryland, 20894, United States
- ZIP Code
- 20894
- Solicitation Number
- NIHLM2015601
- Archive Date
- 8/19/2015
- Point of Contact
- Suet Vu, Phone: 301-496-6546
- E-Mail Address
-
vus@mail.nih.gov
(vus@mail.nih.gov)
- Small Business Set-Aside
- Total Small Business
- Description
- GENERAL INFORMATION INTRODUCTION: This is a Small Business Sources Sought notice. This is NOT a solicitation for proposals, proposal abstracts, or quotations. The purpose of this notice is to obtain information regarding: (1) the availability and capability of qualified small business sources; (2) whether they are small businesses; HUBZone small businesses; service-disabled, veteran-owned small businesses; 8(a) small businesses; veteran-owned small businesses; woman-owned small businesses; or small disadvantaged businesses; and (3) their size classification relative to the North American Industry Classification System (NAICS) code for the proposed acquisition. Your responses to the information requested will assist the Government in determining the appropriate acquisition method, including whether a set-aside is possible. An organization that is not considered a small business under the applicable NAICS code should not submit a response to this notice. The National Institutes of Health (NIH), National Library of Medicine (NLM) is conducting a market survey to help determine the availability and technical capability of qualified small businesses, HUBZone small businesses; service- disabled, veteran-owned small businesses; 8(a) small businesses; veteran-owned small businesses; woman-owned small businesses; or small disadvantaged businesses capable of serving the needs identified below. Background: In previous work done for the National Library of Medicine client/server software has been developed which allows large-image uploading, display, manual region segmentation, and labeling and training of classifiers for automatic region labeling. Motivation for development of this software was the need to provide computer assistance for analysis and region classification of digitized histology images for eventual use in clinical diagnostic and/or biomedical research tasks. Up to the current time, this software, called the Advanced Virtual Microscope, has been used as an R&D experimental tool to upload, display, manually segment, and classify tissue regions in digitized uterine cervix images into classes of epithelium, stroma, and background. Even though the software has been developed for biomedical use, there is in fact no restriction on the types of images which may be used. In order to bring this software to a mature level of development, two tasks have been identified: (1) a rigorous usability analysis should be conducted, and enhancements to user interactions must be implemented; some of these have already been identified and are given in the Proposed Work; and (2) classification performance should be improved; initial experiments using small amounts of training data have yielded classification results on test regions which, using visual interpretation, clearly have too many pixel mis-classifications. We conjecture that methods which allow the easy use of much larger sets of training data may be required. Description of services: Professional services are required to (1) design, implement, and test user interface enhancements to a large-image display and analysis client/server software application previously developed for the National Library of Medicine and to (2) develop algorithms and implementations for classification of biomedical data when the required training data for the algorithms is distributed across multiple sources ("nodes") which may have communication constraints such as limited bandwidth or privacy rules which make processing of all of the data at a central node impractical. In particular services are required to develop and test a distributed Support Vector Machine (SVM) capability which will produce overall classification results by first solving classification sub-problems at each individual node, then combining these sub-problem solutions in an optimal manner, or in a manner supported by technical rationale. The algorithms will be evaluated on a large set of distributed biomedical image data. The client/server software referenced in (1) shall have capability of executing the algorithms developed in (2). Proposed Work: The specific work required consists of two tasks: (1) Implement usability enhancements to the existing Advanced Virtual Microscope (AVM). The contractor will work with the government to identify and implement user interface design changes necessary to make the current AVM system simpler and clearer in operation for a non-technical user. The contractor will meet the following specific requirements, at a minimum: a. Develop how-to videos and link them with main AVM functions to guide users through a hands-on training experience and provide on-demand assistance; establish a wiki page to coordinate inputs from the AVM user community; b. Respond with AVM modifications identified by the government's internal usability analysis group; c. Work with the government to identify use cases and use these as the guiding factors in usability changes; the contractor shall independently propose use cases to the government; d. Remove or hide system functions identified by the government as functions that inhibit the operation of the system by non-technical users; the contractor will propose solutions for removing or hiding such functions; e. Implement a system of alerts/error messages/advisory messages to assist the user in the operation of the system; the contractor will implement this capability in a manner which is, as far as is practical, consistent with what is done in popular software applications; for example, one solution would be to have a status bar where all messages are reported; alerts or errors might be distinguished from advisory messages by including exclamation marks and/or boldface and/or auditory beeps; f. Enhance AVM collaborative annotation capability to allow multiple users, at geographically distinct locations, to jointly view, manipulate, and annotate images; g. Enhance the study management tools in the current AVM to allow a study designer to specify study parameters including study participants and to efficiently communicate study notifications to participants; h. Investigate the feasibility of allowing the use of DICOM files under AVM and, if feasible, implement this support. (2) Implement new classifier capability. In particular, implement capability which allows the easy inclusion of large amounts of training data. Specifically, the contract shall meet the following requirements at a minimum: a. Implement distributed Support Vector Machine (SVM) capability; this will allow the capability for sets of distributed data to be used to train SVM classifiers at distributed sites or "nodes"; the results of these trained classifiers will then be used for global SVM classification; in this scheme, it will not be necessary for the global SVM classifier to have access to the node data; hence, datasets which may be unavailable for direct use for privacy reasons, or impractical to access directly for bandwidth reasons, could nonetheless be used in the global classifier; b. Perform a quantitative evaluation of the above capability on an existing distributed dataset; the contractor will identify, obtain access to, and report on the quantitative results of training and classification with the dataset; since availability of ground truth for classification is a well-known issue in the classification community, the contractor will obtain access to datasets with known ground truth for purposes of evaluating the classification, or the contractor will develop proxy ground truth labels in consultation with the government; c. Develop the algorithms such that they may be invoked, and results viewed, from the AVM system described in Task 1. CONTRACT REQUIREMENTS The contractor will implement specific tasks as defined above during the period of performance. The contractor shall implement these tasks with minimal direction, but in close collaboration with the government. The contents of the deliverables shall be as follows: Deliverable 1: Technical progress report and initial code delivery for Task 1 items, including enhancements to AVM usability and initial capability to carry out distributed SVM classification. Deliverable 2: Technical progress report and final code delivery for Task 2 items, including final enhancements to AVM usability, final capability to carry out distributed SVM classification, and comprehensive report on evaluation of distributed SVM classification capability. It is a goal of the government to test and provide feedback to the Contractor during the development work on the two Tasks, at intervals no longer than three months. For this reason, the Contractor is requested to also provide interim code for each Task at 3- and 9-month points after contract begins, or at time points negotiated with the government. Notice of Government Unlimited Rights to Work First Produced Under This Contract Government rights to work first produced under this contract are established by Federal law including, but not limited to, this specific reference: FAR 42.227-14, Rights in Data - General, (b) (1). Requirement to Notify Government of Proprietary Work Dependencies It is the intent of the Government that all algorithms and code developed under this contract be for public use and benefit, including, but not limited to, internal use by government institutions, use by researchers or other parties collaborating in this work, and public domain release, at the option of the government. The Contractor is required to notify the Government in writing of any dependencies of the deliverables under this contract on proprietary, copyrighted, or patented work that potentially inhibits, restricts, or requires permission for the dissemination of the deliverables to the public, other governmental agencies or research groups, or to any other parties whatsoever. ANTICIPATED PERIOD OF PERFORMANCE: It is anticipated that the period of performance shall be for a 12 month from the date of award. An award is anticipated to be made on or around September 2015. It is anticipated that the contract will be a Firmed-Fixed price type. Interested firms responding to this Sources Sought Notice must adhere to the following: (a) Provide a capability statement demonstrating relevant experience, skills, and ability to fulfill the Government's requirement. The capability statement should be complete and contain sufficient detail for the Government to make an informed decision regarding capabilities; however, the statement should not exceed 10 pages. (b) The capability statement must identify the responder's business type and size; DUNS number; NAICS code, and technical and administrative points of contact, including names, titles, addresses, telephone and fax numbers, and e-mail addresses. (c) The National Library of Medicine (NLM) requires proposals to be submitted via eCPS.: 1) Electronic copy via the NLM electronic Contract Proposal Submission (eCPS) website at https://ecps.nih.gov/nlm. All submissions must be submitted by 1:00pm, Local Prevailing Time, on August 18, 2015. For directions on using eCPS, go to https://ecps.nih.gov/nlm/home/howto and click on "How to Submit." NOTE: To submit your electronic proposal using eCPS, all offerors must have a valid NIH External Directory Account, which provides authentication and serves as a vehicle for secure transmission of documents and communication with the NLM. The NIH External Directory Account registration process may take up to 24 hours to become active. Submission of proposals by facsimile or e-mail is not accepted. EMAILS AND FACSIMILES WILL NOT BE ACCEPTABLE. Disclaimer and Important Notes: This notice does not obligate the Government to award a contract or otherwise pay for the information provided in response. The Government reserves the right to use information provided by respondents for any purpose deemed necessary and legally appropriate. Any organization responding to this notice should ensure that its response is complete and sufficiently detailed to allow the Government to determine the organization's qualifications to perform the work. Respondents are advised that the Government is under no obligation to acknowledge receipt of the information received or provide feedback to respondents with respect to any information submitted. After a review of the responses received, a pre-solicitation synopsis and solicitation may be published in Federal Business Opportunities. However, responses to this notice will not be considered adequate responses to a solicitation. Confidentiality. No proprietary, classified, confidential, or sensitive information should be included in your response. The Government reserves the right to use any non-proprietary technical information in any resultant solicitation(s).
- Web Link
-
FBO.gov Permalink
(https://www.fbo.gov/spg/HHS/NIH/OAM/NIHLM2015601/listing.html)
- Place of Performance
- Address: Bethesda, Maryland, 20894, United States
- Zip Code: 20894
- Zip Code: 20894
- Record
- SN03836005-W 20150814/150813000136-499018b7629199c6c06b813cc8dcda36 (fbodaily.com)
- Source
-
FedBizOpps Link to This Notice
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