Distortions of the magnetic field, such as those caused by susceptibility artifacts and peripheral magnetic field warping, can limit geometric precision in the use of magnetic resonance (MR) imaging in stereotactic procedures. The authors have routinely found systematic error in MR stereotactic coordinates with a median of 4 mm compared to computerized tomography (CT) coordinates. This error may place critical neural structures in jeopardy in sme procedures. A description is given of an image fusion technique that uses a chamfer matching algorithm; the advantages of MR imaging in anatomical definition are combined with the geometric precision of CT, while eliminating most of the anatomical spatial distortion of stereotactic MR imaging. A stereotactic radiosurgical case is presented in which the use of MR localization alone would have led to both irradiation of vital neural structures outside the desired target volume and underdose of the intended target volume. The image fusion approach allows for the use of MR imaging, combined with stereotactic CT, as a reliable localizing technique for stereotactic neurosurgery and radiosurgery.
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http://dx.doi.org/10.3171/jns.1995.83.2.0271 | DOI Listing |
Int Ophthalmol
January 2025
Beyoglu Eye Training and Research Hospital, University of Health Sciences, Bereketzade Camii Sk. No:2 Beyoğlu, 34421, Istanbul, Turkey.
Background: To evaluate the efficacy and safety of intravitreal injections of 4 mg (high dose) of aflibercept in treatment-naive patients with neovascular AMD(nAMD) with treat and extend(TREX) dosing regimens, and to determine the frequency of injections.
Methods: In this interventional, retrospective study a total of 15 eyes of 14 patients (eight female and 9 male) with nAMD were included. All patients were examined and OCT imaging was performed at the time of initial presentation, on the day of each injection and at subsequent follow-up visits.
Transl Lung Cancer Res
December 2024
Department of Radiology, Second Affiliated Hospital of Naval Medical University, Shanghai, China.
Background: Spread through air spaces (STAS) in lung adenocarcinoma (LUAD) is a distinct pattern of intrapulmonary metastasis where tumor cells disseminate within the pulmonary parenchyma beyond the primary tumor margins. This phenomenon was officially included in the World Health Organization (WHO)'s classification of lung tumors in 2015. STAS is characterized by the spread of tumor cells in three forms: single cells, micropapillary clusters, and solid nests.
View Article and Find Full Text PDFFront Bioeng Biotechnol
January 2025
Department of Rheumatology and Immunology, Beijing Hospital, National Centre of Gerontology, Beijing, China.
Background: Knee osteoarthritis (KOA) constitutes the prevailing manifestation of arthritis. Radiographs function as a common modality for primary screening; however, traditional X-ray evaluation of osteoarthritis confronts challenges such as reduced sensitivity, subjective interpretation, and heightened misdiagnosis rates. The objective of this investigation is to enhance the validation and optimization of accuracy and efficiency in KOA assessment by utilizing fusion deep learning techniques.
View Article and Find Full Text PDFFront Oncol
January 2025
Department of Hepatobiliary Surgery, General Hospital of Ningxia Medical University, Yinchuan, China.
Aim: To develop a habitat imaging method for preoperative prediction of early postoperative recurrence of hepatocellular carcinoma.
Methods: A retrospective cohort study was conducted to collect data on 344 patients who underwent liver resection for HCC. The internal subregion of the tumor was objectively delineated and the clinical features were also analyzed to construct clinical models.
Dent Traumatol
January 2025
Department of Endodontology, Maurice and Gabriela Goldschleger School of Dental Medicine, Tel Aviv University, Tel Aviv, Israel.
Background/aim: To explore transfer learning (TL) techniques for enhancing vertical root fracture (VRF) diagnosis accuracy and to assess the impact of artificial intelligence (AI) on image enhancement for VRF detection on both extracted teeth images and intraoral images taken from patients.
Materials And Methods: A dataset of 378 intraoral periapical radiographs comprising 195 teeth with fractures and 183 teeth without fractures serving as controls was included. DenseNet, ConvNext, Inception121, and MobileNetV2 were employed with model fusion.
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