[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-119905-en":3,"doc-seo-119905-105":30,"detail-sidebar-cat-0-en-105":92},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},119905,3848291630094,"Emma Wilson","https://eur-avatar.wpscdn.com/davatar_085a072bc5b1113ac321206ff7593b45",8,"Research & Report","Machine Learning guided Advanced Image Reconstruction in Photo Magnetic Imaging - Dissertation","This dissertation investigates machine-learning–guided advanced image reconstruction for Photo Magnetic Imaging (PMI), aiming to improve the accuracy and robustness of reconstructing internal targets from PMI measurements. It develops and validates a workflow that includes PMI data generation, direct detection via machine learning, region-of-interest localization with precision improvement, and preprocessing for multi-absorption signals. The study analyzes class imbalance and multilabel classification, evaluates region-of-interest and ROI-precision pipelines, and discusses results across target properties such as absorption, size, and separation, culminating in conclusions and future research directions.","UC Irvine  \nUC Irvine Electronic Theses and Dissertations  \nTitle  \nMachine Learning guided advanced Image Reconstruction in Photo Magnetic Imaging  \nPermalink  \n[https://escholarship.org/uc/item/7p76t431](https://escholarship.org/uc/item/7p76t431)  \nAuthor  \nSaraswatula, Janaki Sankirthana  \nPublication Date  \n2023  \nPeer reviewed|Thesis/dissertation  \n[eScholarship.org](eScholarship.org) Powered by the California Digital Library  \nUniversity of California  \nUNIVERSITY OF CALIFORNIA,  \nIRVINE  \nMachine Learning guided Advanced Image Reconstruction  \nin Photo Magnetic Imaging  \nDISSERTATION  \nSubmitted in partial satisfaction of the requirements for  \nthe degree of  \nMASTER OF SCIENCE  \nin ELECTRICAL AND COMPUTER ENGINEERING  \nby  \nJanaki Sankirthana Saraswatula  \nThesis Committee:  \nGultekin Gulsen, Ph.D, Chair Terence Sanger, M.D  \nGlenn Healey, Ph.D  \nSupervisor: Farouk Nouizi, Ph.D  \n2023  \nTable of Contents  \nA. INTRODUCTION .................................................................................................................. 8  \nB. BACKGROUND .................................................................................................................. 10  \nI. Medical Imaging ................................................................................................................ 10  \nII. Diffuse Optical Imaging Techniques ............................................................................. 11  \n1. Fluorescence Tomography ......................................................................................... 11  \n2. Diffuse Optical Tomography...................................................................................... 11  \nIII. Photo Magnetic Imaging (PMI) ..................................................................................... 13  \nIV. PMI Forward Problem.................................................................................................... 15  \n1. Propagation of light in the tissue ................................................................................ 15  \n2. Propagation of heat in the tissue ................................................................................. 16  \n3. PMI forward Problem ................................................................................................. 16  \n4. PMI Inverse Problem .................................................................................................. 17  \nC. Background: Image Processing and Machine Learning .................................................... 20  \nV. Gray Level transformations in an Image........................................................................ 20  \n1. Gray Level Thresholding ............................................................................................ 20  \n2. Image Transformation functions ................................................................................ 21  \n3. Hough Space and Hough Transform .......................................................................... 22  \nVI. Machine Learning and Deep Learning........................................................................... 24  \n1. Loss or Cost Functions ............................................................................................... 25  \nD. Methodology ......................................................................................................................... 32  \nI. PMI Data Generation ......................................................................................................... 32  \nII. Direct Detection Using Machine Learning .................................................................... 36  \n2. Understanding the class imbalance and multilabel classification .............................. 37  \nIII. Region of Interest Localizer and Precision Improver .................................................... 39  \nIV. Precision Improvement ........................................................................","cbCaisUX5LrdXTbu","https://ap.wps.com/l/cbCaisUX5LrdXTbu","pdf",2847049,1,73,"English","en",105,"# A. INTRODUCTION\n# B. BACKGROUND\n## Medical Imaging\n## Diffuse Optical Imaging Techniques\n## Photo Magnetic Imaging (PMI)\n# C. Background: Image Processing and Machine Learning\n## Gray Level transformations in an Image\n## Machine Learning and Deep Learning\n# D. Methodology\n## PMI Data Generation\n## Direct Detection Using Machine Learning\n## Region of Interest Localizer and Precision Improver\n## Precision Improvement\n## The Testing procedure\n## Challenges\n## Preprocessing for Multi-Absorption Data\n# E. Results and Discussion\n## Representational Diagrams for Results\n## Results obtained using the ROI Network\n## Results obtained using ROI-Precision pipeline\n# F. Conclusion and Future Work","[{\"question\":\"What is the main focus of the dissertation?\",\"answer\":\"The dissertation focuses on machine learning–guided advanced image reconstruction for Photo Magnetic Imaging (PMI), emphasizing improved reconstruction quality from PMI data.\"},{\"question\":\"Which problem domains are covered in the background?\",\"answer\":\"It covers medical imaging, diffuse optical imaging techniques, and PMI forward and inverse problems, and then transitions to image processing and machine learning concepts.\"},{\"question\":\"How are results evaluated in the methodology?\",\"answer\":\"Results are evaluated through a testing procedure and comparisons across pipelines such as the ROI network and an ROI-precision approach, analyzing effects of absorption, inclusion size, and distances between inclusions.\"}]","Machine Learning guided Advanced Image Reconstruction in Photo Magnetic Imaging - Dissertation | PDF",1785726928,184,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":87,"head_meta":89,"extra_data":91,"updated_unix":28},"machine-learning-guided-advanced-image-reconstruction-in-photo-magnetic-imaging-dissertation","",{"@graph":36,"@context":86},[37,54,69],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/machine-learning-guided-advanced-image-reconstruction-in-photo-magnetic-imaging-dissertation/119905/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":63,"encodingFormat":61,"isAccessibleForFree":64,"interactionStatistic":65},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-04","2026-08-03",true,{"@type":66,"interactionType":67,"userInteractionCount":20},"InteractionCounter",{"@type":68},"ViewAction",{"@type":70,"mainEntity":71},"FAQPage",[72,78,82],{"name":73,"@type":74,"acceptedAnswer":75},"What is the main focus of the dissertation?","Question",{"text":76,"@type":77},"The dissertation focuses on machine learning–guided advanced image reconstruction for Photo Magnetic Imaging (PMI), emphasizing improved reconstruction quality from PMI data.","Answer",{"name":79,"@type":74,"acceptedAnswer":80},"Which problem domains are covered in the background?",{"text":81,"@type":77},"It covers medical imaging, diffuse optical imaging techniques, and PMI forward and inverse problems, and then transitions to image processing and machine learning concepts.",{"name":83,"@type":74,"acceptedAnswer":84},"How are results evaluated in the methodology?",{"text":85,"@type":77},"Results are evaluated through a testing procedure and comparisons across pipelines such as the ROI network and an ROI-precision approach, analyzing effects of absorption, inclusion size, and distances between inclusions.","https://schema.org",{"og:url":52,"og:type":88,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":90,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":93},[94,98,102,106,111,116,121,124,129,132,136],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":95,"show_sort_weight":96,"slug":97},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":99,"show_sort_weight":100,"slug":101},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":103,"show_sort_weight":104,"slug":105},"Exam",70,"exam",{"id":107,"doc_module":4,"doc_module_name":46,"category_name":108,"show_sort_weight":109,"slug":110},5,"Comic",60,"comic",{"id":112,"doc_module":4,"doc_module_name":46,"category_name":113,"show_sort_weight":114,"slug":115},6,"Technology",50,"technology",{"id":117,"doc_module":4,"doc_module_name":46,"category_name":118,"show_sort_weight":119,"slug":120},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":122,"slug":123},30,"research-report",{"id":125,"doc_module":4,"doc_module_name":46,"category_name":126,"show_sort_weight":127,"slug":128},9,"Religion & Spirituality",20,"religion-spirituality",{"id":127,"doc_module":4,"doc_module_name":46,"category_name":130,"show_sort_weight":127,"slug":131},"World Cup","world-cup",{"id":133,"doc_module":4,"doc_module_name":46,"category_name":134,"show_sort_weight":133,"slug":135},10,"Lifestyle","lifestyle",{"id":137,"doc_module":4,"doc_module_name":46,"category_name":138,"show_sort_weight":107,"slug":139},19,"General","general"]