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001-es BibID:BIBFORM100559
035-os BibID:(cikkazonosító)102350
Első szerző:Riemma, Gaetano
Cím:The role of hysteroscopy in reproductive surgery : today and tomorrow / Riemma Gaetano, Vitale Salvatore Giovanni, Manchanda Rahul, Rathore Aayushi, Török Péter, De Angelis Carlo, Urman Bulent, Sareri Marco Iraci, La Verde Marco, Carugno Jose, De Franciscis Pasquale, Tesarik Jan
Dátum:2022
ISSN:2468-7847
Megjegyzések:During the last decades, the number of couples with reproductive issues has substantially increased. Many different factors are implicated in reproductive failure, including uterine factors. Endometrial pathologies, such as endometrial polyps, hyperplasia, endometritis, and Mullerian anomalies, can also hinder embryo implantation. Hysteroscopy remains the gold standard for the evaluation and treatment of intrauterine pathology. Over the last few years, advances in hysteroscopic instrumentations and surgical techniques have significantly evolved, the refinement in technology, miniaturization of instruments, and improved image quality have rendered hysteroscopy a more patient and user-friendly procedure that has enhanced its use in reproductive medicine. Nowadays, hysteroscopy is essential in the evaluation and treatment of women with infertility. This article underscores the major technological breakthroughs achieved over the last few years with emphasis on the role of artificial intelligence, augmented reality, and 3D hysteroscopy, which can set new benchmarks in hysteroscopy applied to reproductive medicine.
Tárgyszavak:Orvostudományok Klinikai orvostudományok idegen nyelvű folyóiratközlemény külföldi lapban
folyóiratcikk
Hysteroscopy
portable hysteroscope
tissue retrieval system
3D hysteroscopy
clinical pregnancy
IVF
Megjelenés:Journal of Gynecology Obstetrics and Human Reproduction. - 51 : 4 (2022), p. 1-5. -
További szerzők:Vitale, Salvatore Giovanni Manchanda, Rahul Rathore, Aayushi Török Péter (1975-) (szülész-nőgyógyász) De Angelis, Carlo Urman, Bulent Sareri, Marco Iraci La Verde, Marco Carugno, Jose De Franciscis, Pasquale Tesarik, Jan
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001-es BibID:BIBFORM071334
Első szerző:Török Péter (szülész-nőgyógyász)
Cím:Differentiating tissues and organs in endoscopic images using a convolutional neural network / Török Péter, Lampé Rudolf, Harangi Balázs, Lőrincz Judit
Dátum:2017
ISSN:0268-1161
Megjegyzések:TitleDifferentiating tissues and organs in endoscopic images using a convolutional neural networkStudy questionIs it possible to identify different tissues and organs during endoscopy supported by a software.Summary answer During the learning curve of laparoscopy trainees can get help in differentiating tissues by an automated digital image processing based decision support systemWhat is known already Endoscopy surgery is the part of everyday work of surgeon. In an experienced hand provides less postoperative morbidity, complications and the time periods of hospital stay and returning to normal activity, so it has a lot of advantages compared to the laparotomy.Opposing to open-surgery, the recognition of organs is rather difficult in laparoscopy because of the lack of the tactile information. Knowing detailed anatomy, having experience letting us to recognize structures in the abdominal cavity. Because of the anatomical variations, tissue identification is not always sure relying on the visual information.Study design, size, duration COur dataset has been collected retrospectively during 35 different gynecological endoscopic operations at the Department of Obstetrics and Gynecology of the University of Debrecen. The videos have been recorded by a high definition 1-MOS endoscopic camera at 30 frames/sec rate and resolution of 1920?1080 pixels.Participants/materials, setting, methods Data of patients scheduled for gynecological endoscopic operations are analyzed. The medical expert or an assistant should manually mark the region of interest. Then, the maximum number of sub-images of size 224?224 pixels are cut off along the axis from the video frame. Finally, the classification problem is solved automatically using a convolutional neural network with the resulted labels are pinned on the corresponding organs in the video frame.Main results and the role of chance We have presented an approach to develop an application, which helps medical experts with performing endoscopic surgeries. Our effort primarily addressed the drawback of losing tactile information during key-hole surgery in the recognition of different organs. To address this problem, we have developed a semi-automatic tool, which requires a manual annotation regarding the axis of the interested organs first. Then, several sub-images covering the selected organs are extracted and classified by a fine-tuned GoogLeNet convolutional neural network.The classification performance of the fine-tuned GoogLeNet model on our test dataset considering the top-1 error rate is 0.193 at sub-image level. That is, 403 out of the 500 test images have been classified correctly. However, notice that these sub-images are only small, non-overlapping segments of the interested organs. That is, it is reasonable to fuse these label information for recognizing the corresponding organ. To do so, we have applied the simple majority-voting rule on the 4-5 labels supplied by the sub-images for the same organ. In this way, our proposed approach has reached 94.2% final accuracy regarding this binary classification task.Limitations, reasons for cautionOur collected dataset is relatively small with containing insufficient number of images to train a complex neural network, so we should extend the size of our dataset.Wider implications of the findings Using the software made by the results of the study, accuracy of the tissue/organ recognition could be increased during training laparoscopic technique, or for the experts as well.Study funding/competing interest(s) This work was supported in part by the projects GINOP-2.1.1-15-2015-00376 and VKSZ 14-1-2015-0072, SCOPIA: Development of diagnostic tools based on endoscope technology supported by the European Union, co-financed by the European Social Fund.
Tárgyszavak:Orvostudományok Klinikai orvostudományok idézhető absztrakt
laparoszkópia
endoszkópia
mélytanulás
konvolúcionális neurális hálózat
szövetfelismerés
Megjelenés:Human Reproduction 32 : suppl. 1 (2017), p. 487. -
További szerzők:Lampé Rudolf (1983-) (szülész-nőgyógyász) Harangi Balázs (1986-) (programtervező matematikus) Lőrincz Judit (1988-) (általános orvos)
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3.

001-es BibID:BIBFORM039086
Első szerző:Török Péter (szülész-nőgyógyász)
Cím:A novel method of selective chromopertubation at office hysteroscopy / Török P., Jakab A., Major T.
Dátum:2011
ISSN:0268-1161
Tárgyszavak:Orvostudományok Klinikai orvostudományok idézhető absztrakt
Megjelenés:Human Reproduction 26 : Suppl. 1. (2011), p. i12. -
További szerzők:Jakab Attila (1964-) (szülész-nőgyógyász, endokrinológus) Major Tamás (1963-) (szülész-nőgyógyász)
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4.

001-es BibID:BIBFORM110695
035-os BibID:(cikkazonosító)102588 (Scopus)85153232429 (WoS)000990464300001
Első szerző:Vitale, Salvatore Giovanni
Cím:Endometrial Biopsy : Indications, Techniques and Recommendations. An Evidence-Based Guideline for Clinical Practice / Vitale Salvatore Giovanni, Buzzaccarini Giovanni, Riemma Gaetano, Pacheco Luis Alonso, Sardo Attilio Di Spiezio, Carugno Jose, Chiantera Vito, Török Peter, Noventa Marco, Haimovich Sergio, De Franciscis Pasquale, Perez-Medina Tirso, Angioni Stefano, Lagana Antonio Simone
Dátum:2023
ISSN:2468-7847
Megjegyzések:This practice guideline provides updated evidence for the gynecologist who performs endometrial biopsy (EB) in gynecologic clinical practice. An international committee of gynecology experts developed the recommendations according to AGREE Reporting Guideline. An adequate tissue sampling is mandatory when performing an EB. Blind methods should not be first choice in patients with suspected endometrial malignancy. Hysteroscopy is the targeted-biopsy method with highest diagnostic accuracy and cost-effectiveness. Blind suction techniques are not reliable for the diagnosis of endometrial polyps. In low resources settings, and in absence of the capacity to perform office hysteroscopy, blind techniques could be used for EB. Hysteroscopic punch biopsy allows to collect only limited amount of endometrial tissue. grasp biopsy technique should be considered first choice in reproductive aged women, bipolar electrode chip biopsy should be preferred with hypotrophic or atrophic endometrium. EB is required for the final diagnosis of chronic endometritis. There is no consensus regarding which endometrial thickness cut-off should be used for recommending EB in asymptomatic postmenopausal women. EB should be offered to young women with abnormal uterine bleeding and risk factors for endometrial carcinoma. Endometrial pathology should be excluded with EB in nonobese women with unopposed hyperestrogenism. Hysteroscopy with EB is useful in patients with abnormal bleeding even without sonographic evidence of pathology. EB has high sensitivity for detecting intrauterine pathologies. In postmenopausal women with uterine bleeding, EB is recommended. Women with sonographic endometrial thickness > 4mm using tamoxifen should undergo hysteroscopic EB.
Tárgyszavak:Orvostudományok Klinikai orvostudományok idegen nyelvű folyóiratközlemény külföldi lapban
folyóiratcikk
Hysteroscopy
Practical guidelines
Endometrium
Endometrial biopsy
Megjelenés:Journal of Gynecology Obstetrics and Human Reproduction. - 52 : 6 (2023), p. 1-7. -
További szerzők:Buzzaccarini, Giovanni Riemma, Gaetano Pacheco, Luis Alonso Sardo, Attilio Di Spiezio Carugno, Jose Chiantera, Vito Török Péter (1975-) (szülész-nőgyógyász) Noventa, Marco Haimovich, Sergio De Franciscis, Pasquale Perez-Medina, Tirso Angioni, Stefano Laganà, Antonio Simone
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