A Review of Hyperspectral Imaging in Neurosurgery: Datasets and Computational Approaches

BildiriYalnız künye

Özet

Hyperspectral imaging (HSI) is an imaging method that differs from traditional methods by recording the light reflection and absorption properties of each point across a wide color range. HSI enables the non-invasive determination of chemical and structural differences in tissues with high accuracy. In the domain of medicine, hyperspectral imaging represents a novel methodology that facilitates novel approaches in brain surgery, including the distinction of tumors and blood vessels, cancer diagnosis, and the monitoring of tissue oxygen levels and blood flow during surgical procedures. Additionally, hyperspectral imaging has a wide range of applications in various fields, including agriculture, food, environment, geology, and defense.This review comprehensively examines current datasets, application areas, and computational approaches related to the use of hyperspectral imaging technology in brain surgery. HSI enables the precise differentiation of different brain tissues such as tumors, vessels, functional areas, and the spine by collecting data across a wide spectral band range for each pixel. Recent studies in the literature demonstrate that machine learning and deep learning-based methods can achieve high accuracy rates in tissue segmentation and the detection of pathological structures in brain surgery. Additionally, datasets developed at different centers and involving various patient groups provide an important foundation for enhancing the clinical efficacy of HSI.While HSI boasts significant advantages in terms of its non-invasiveness and real-time analysis potential, which benefit surgeons during intraoperative decision-making processes, challenges such as data size, computational costs, and device integration pose barriers to its routine use. In the future, it is anticipated that these limitations will be overcome through the development of efficient algorithms, AI-supported systems, and multi-center validation studies. In conclusion, HSI technology exhibits considerable potential to become a standard intraoperative instrument in neurosurgery, driven by advancing computational methods and increasing clinical validation.

Anahtar Kelimeler

RDL Kalıcı Bağlantı (PID)
https://rdlopen.rawdatalibrary.net/r/kostu/10202Resmi atıflarda kullanılan kalıcı adres
İndeks kayıtları
Kaydın indeks veri tabanlarındaki sayfası (aktarımda alınan kayıt numarasıyla). Erişim, indeksin kendi koşullarına bağlıdır.
Atıflar
Scopus
1
Her kaynağın kendi saydığı toplam atıf; aktarım ve zenginleştirme sırasında alındı.
Tam Kayıt
AlanDeğerDil
dc.contributor.authorOzturk, Candide
dc.contributor.authorEker, Ayse Gul
dc.contributor.authorPehlivanoglu, Meltem Kurt
dc.contributor.authorKaraduman, Ismet
dc.contributor.authorOlcer, Ercan
dc.contributor.authorDuru, Nevcihan
dc.contributor.authorDundar, Tolga Turan
dc.contributor.authorMutluer, Ahmet Serdar
dc.contributor.authorDogan, Ihsan
dc.contributor.authorEricek, Omer Burak
dc.contributor.editorAdali, E.
dc.date.accessioned2026-10-27T20:41:05.214779011Z
dc.date.available2026-10-27T20:41:05.214779011Z
dc.date.issued2025
dc.description.abstractHyperspectral imaging (HSI) is an imaging method that differs from traditional methods by recording the light reflection and absorption properties of each point across a wide color range. HSI enables the non-invasive determination of chemical and structural differences in tissues with high accuracy. In the domain of medicine, hyperspectral imaging represents a novel methodology that facilitates novel approaches in brain surgery, including the distinction of tumors and blood vessels, cancer diagnosis, and the monitoring of tissue oxygen levels and blood flow during surgical procedures. Additionally, hyperspectral imaging has a wide range of applications in various fields, including agriculture, food, environment, geology, and defense.This review comprehensively examines current datasets, application areas, and computational approaches related to the use of hyperspectral imaging technology in brain surgery. HSI enables the precise differentiation of different brain tissues such as tumors, vessels, functional areas, and the spine by collecting data across a wide spectral band range for each pixel. Recent studies in the literature demonstrate that machine learning and deep learning-based methods can achieve high accuracy rates in tissue segmentation and the detection of pathological structures in brain surgery. Additionally, datasets developed at different centers and involving various patient groups provide an important foundation for enhancing the clinical efficacy of HSI.While HSI boasts significant advantages in terms of its non-invasiveness and real-time analysis potential, which benefit surgeons during intraoperative decision-making processes, challenges such as data size, computational costs, and device integration pose barriers to its routine use. In the future, it is anticipated that these limitations will be overcome through the development of efficient algorithms, AI-supported systems, and multi-center validation studies. In conclusion, HSI technology exhibits considerable potential to become a standard intraoperative instrument in neurosurgery, driven by advancing computational methods and increasing clinical validation.
dc.identifier.doi10.1109/ubmk67458.2025.11207035
dc.identifier.endpage968
dc.identifier.issn2521-1641
dc.identifier.issue2025
dc.identifier.scopus2-s2.0-105030838713
dc.identifier.startpage963
dc.identifier.urihttps://rdlopen.rawdatalibrary.net/r/kostu/10202
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relation.conference10th International Conference on Computer Science and Engineering, UBMK 2025
dc.relation.ispartofInternational Conference on Computer Science and Engineering, UBMK
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectbrain surgery
dc.subjectdeep learning
dc.subjecthyperspectral imaging
dc.subjectneurosurgery
dc.subjecttissue classification
dc.subject.otherBlood
dc.subject.otherBlood vessels
dc.subject.otherBrain
dc.subject.otherClassification (of information)
dc.subject.otherDecision making
dc.subject.otherDiagnosis
dc.subject.otherHyperspectral imaging
dc.subject.otherLearning systems
dc.subject.otherNoninvasive medical procedures
dc.subject.otherTissue engineering
dc.subject.otherTransplantation (surgical)
dc.subject.otherTumors
dc.subject.otherBrain surgery
dc.subject.otherComputational approach
dc.subject.otherDeep learning
dc.subject.otherHigh-accuracy
dc.subject.otherHyperSpectral
dc.subject.otherHyperspectral imaging technologies
dc.subject.otherImaging method
dc.subject.otherIntra-operative
dc.subject.otherReflection properties
dc.subject.otherTissue classification
dc.subject.otherNeurosurgery
dc.titleA Review of Hyperspectral Imaging in Neurosurgery: Datasets and Computational Approaches
dc.typeConference Object
rdl.citation.scopus1
rdl.conference.date17 September 2025 through 21 September 2025
rdl.conference.placeIstanbul
rdl.oa.statusclosed
rdl.source.indexSCOPUS