{"id":"https://openalex.org/W4408110331","doi":"https://doi.org/10.1201/9781003606185-34","title":"A survey on brain tumor detection from MRI using deep learning","display_name":"A survey on brain tumor detection from MRI using deep learning","publication_year":2025,"publication_date":"2025-03-03","ids":{"openalex":"https://openalex.org/W4408110331","doi":"https://doi.org/10.1201/9781003606185-34"},"language":"en","primary_location":{"id":"doi:10.1201/9781003606185-34","doi":"https://doi.org/10.1201/9781003606185-34","is_oa":false,"landing_page_url":"https://doi.org/10.1201/9781003606185-34","pdf_url":null,"source":{"id":"https://openalex.org/S4306463075","display_name":"CRC Press eBooks","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/P4310320584","host_organization_name":"CRC Press","host_organization_lineage":["https://openalex.org/P4310320584","https://openalex.org/P4310320547"],"host_organization_lineage_names":["CRC Press","Taylor & Francis"],"type":"ebook platform"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Digital Transformation and Sustainability of Business","raw_type":"book-chapter"},"volume":{"id":"https://openalex.org/W4408090944","display_name":"Digital Transformation and Sustainability of Business"},"type":"book-chapter","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5116486129","display_name":"Nirav Ranpara","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nirav Ranpara","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056304227","display_name":"Chetan Shingadiya","orcid":"https://orcid.org/0000-0002-2425-3534","observed_orcids":["https://orcid.org/0000-0002-2425-3534"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chetan Shingadiya","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5051009499","display_name":"Krishna Chaithanya","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Krishna Chaithanya","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.03721374,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"144","last_page":"147"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12702","display_name":"Brain Tumor Detection and Classification","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T12702","display_name":"Brain Tumor Detection and Classification","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.0,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.0,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/brain-tumor-detection","display_name":"brain tumor detection","score":1.0},{"id":"https://openalex.org/keywords/magnetic-resonance-imaging","display_name":"magnetic resonance imaging","score":0.7549999952316284},{"id":"https://openalex.org/keywords/deep-learning","display_name":"deep learning","score":0.6740000247955322},{"id":"https://openalex.org/keywords/convolutional-neural-networks","display_name":"convolutional neural networks","score":0.9350000023841858},{"id":"https://openalex.org/keywords/recurrent-neural-networks","display_name":"recurrent neural networks","score":0.8090000152587891},{"id":"https://openalex.org/keywords/autoencoder","display_name":"autoencoder","score":0.996999979019165},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"image segmentation","score":0.7160000205039978},{"id":"https://openalex.org/keywords/data-preprocessing","display_name":"data preprocessing","score":0.640999972820282},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"noise reduction","score":0.8539999723434448},{"id":"https://openalex.org/keywords/data-augmentation","display_name":"data augmentation","score":0.9990000128746033},{"id":"https://openalex.org/keywords/treatment-response-prediction","display_name":"treatment response prediction","score":0.7540000081062317},{"id":"https://openalex.org/keywords/tumor-growth-prediction","display_name":"tumor growth prediction","score":0.8059999942779541},{"id":"https://openalex.org/keywords/interpretability","display_name":"interpretability","score":0.7400000095367432},{"id":"https://openalex.org/keywords/dataset-bias","display_name":"data bias","score":0.4359999895095825}],"concepts":[{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5102829933166504},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4553844928741455},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.43922582268714905},{"id":"https://openalex.org/C2779130545","wikidata":"https://www.wikidata.org/wiki/Q233309","display_name":"Brain tumor","level":2,"score":0.4296149015426636},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.38173961639404297},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.3732416033744812},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.33399754762649536},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.1543257236480713}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1201/9781003606185-34","doi":"https://doi.org/10.1201/9781003606185-34","is_oa":false,"landing_page_url":"https://doi.org/10.1201/9781003606185-34","pdf_url":null,"source":{"id":"https://openalex.org/S4306463075","display_name":"CRC Press eBooks","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/P4310320584","host_organization_name":"CRC Press","host_organization_lineage":["https://openalex.org/P4310320584","https://openalex.org/P4310320547"],"host_organization_lineage_names":["CRC Press","Taylor & Francis"],"type":"ebook platform"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Digital Transformation and Sustainability of Business","raw_type":"book-chapter"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Good health and well-being","score":0.5683000087738037,"id":"https://metadata.un.org/sdg/3"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W7218209969","https://openalex.org/W4362499019","https://openalex.org/W4415818857","https://openalex.org/W4390550844","https://openalex.org/W4214937897","https://openalex.org/W3185384151","https://openalex.org/W7220589010","https://openalex.org/W4414711543","https://openalex.org/W4395040156","https://openalex.org/W7162447625"],"abstract_inverted_index":{"To":[0],"maximize":[1],"patient":[2],"outcomes,":[3],"brain":[4,45,172],"tumors":[5],"must":[6],"be":[7],"identified":[8],"as":[9,11,20,67,125,154,161],"soon":[10],"possible":[12,137],"and":[13,73,78,87,96,108,116,132,139,158],"with":[14,120],"precision.":[15],"Deep":[16],"learning":[17,42,63,170],"has":[18],"emerged":[19],"a":[21],"viable":[22],"technique":[23],"for":[24,44,84],"this":[25,54],"type":[26],"of":[27,34,40,61,128,168],"medical":[28,49],"imaging":[29,50],"analysis,":[30],"despite":[31],"the":[32,58,114,126,165],"drawbacks":[33],"older":[35],"methods.":[36],"A":[37],"thorough":[38],"investigation":[39],"deep":[41,62,122,169],"techniques":[43],"tumor":[46,85,159,173],"identification":[47],"from":[48],"is":[51],"provided":[52],"by":[53],"survey.":[55],"We":[56],"examine":[57,91],"wide":[59],"range":[60],"architectures":[64],"used,":[65],"such":[66,124,153],"autoencoders,":[68],"recurrent":[69],"neural":[70,75],"networks":[71,76],"(RNNs),":[72],"convolutional":[74],"(CNNs),":[77],"assess":[79],"how":[80,98],"well":[81],"they":[82,99],"work":[83],"recognition":[86],"segmentation.":[88],"Next,":[89],"we":[90,149,162],"important":[92],"data":[93,109],"pre-processing":[94],"methods":[95],"show":[97],"improve":[100],"model":[101],"performance,":[102],"including":[103],"image":[104],"segmentation,":[105],"noise":[106],"reduction,":[107],"augmentation.":[110],"The":[111],"survey":[112],"recognizes":[113],"difficulties":[115],"constraints":[117],"that":[118],"come":[119],"using":[121],"learning,":[123],"availability":[127],"data,":[129],"bias,":[130],"interpretability,":[131],"processing":[133],"cost.":[134],"It":[135],"describes":[136],"fixes":[138],"current":[140],"research":[141],"projects":[142],"aimed":[143],"at":[144],"resolving":[145],"these":[146],"problems.":[147],"Lastly,":[148],"cover":[150],"advanced":[151],"applications":[152],"treatment":[155],"response":[156],"prediction":[157],"growth":[160],"map":[163],"out":[164],"future":[166],"paths":[167],"in":[171],"detection.":[174]},"counts_by_year":[],"updated_date":"2026-10-10T09:11:00.788812","created_date":"2025-03-04T00:00:00"}